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Image segmentation, Standards, Task analysis, Pathology,
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Glands, Task analysis, Image segmentation, Adaptation models,
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Task analysis, Annotations, Histopathology,
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2110
Uncertainty, Feature extraction, Histograms, Training,
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Pathology, Image segmentation, Decoding, Decision trees,
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Glands, Image segmentation, Semantics, Feature extraction,
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Image segmentation, Uncertainty, Histopathology, Predictive models,
Standards, Training, Solid modeling, interpretability
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Noise measurement, Training, Histopathology, Noise robustness,
Image classification, Data models, Predictive models,
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2205
Noise measurement, Annotations, Training, Biomedical imaging,
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2206
2-D RNN, Conditional random field, Detail preservation,
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Zhang, L.J.[Li-Juan],
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2209
Feature extraction, Computational modeling, Training,
Adaptation models, Biomedical imaging, Annotations, Deep learning,
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2209
Image registration, Strain, Convolutional neural networks,
Task analysis, Image resolution, Feature extraction,
unsupervised learning
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IEEE DOI
2209
Pathology, Image segmentation, Training, Lesions, Biomedical imaging,
Generators, Measurement, Medical image synthesis,
label noise
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IEEE DOI
2212
Histopathology, Training, Task analysis,
Convolutional neural networks, Deep learning, Correlation, active learning
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Han, X.[Xiao],
Knowledge-Based Representation Learning for Nucleus Instance
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MedImg(41), No. 12, December 2022, pp. 3939-3951.
IEEE DOI
2212
Pathology, Task analysis, Feature extraction, Data models,
Representation learning, Labeling, Annotations, Triplet learning,
digital pathology
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Jia, C.[Chang],
Li, Y.[Yang],
Zhang, X.L.[Xian-Li],
Hong, B.Y.[Bang-Yang],
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Gong, T.L.[Tie-Liang],
Wang, C.B.[Chun-Bao],
Meng, D.Y.[De-Yu],
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Li, C.[Chen],
Unsupervised Representation Learning for Tissue Segmentation in
Histopathological Images: From Global to Local Contrast,
MedImg(41), No. 12, December 2022, pp. 3611-3623.
IEEE DOI
2212
Task analysis, Image segmentation, Annotations, Decoding, Tumors,
Representation learning, Cancer, Contrastive learning, superpixel
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Yang, M.[Mei],
Xie, Z.Y.[Zhi-Ying],
Wang, Z.X.[Zhao-Xia],
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Zhang, J.[Jue],
Su-MICL: Severity-Guided Multiple Instance Curriculum Learning for
Histopathology Image Interpretable Classification,
MedImg(41), No. 12, December 2022, pp. 3533-3543.
IEEE DOI
2212
Histopathology, Lesions, Training, Diseases, Annotations,
Task analysis, Supervised learning, Multiple instance learning,
interpretability
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Chen, Y.[Yi],
Dong, Y.[Yang],
Si, L.[Lu],
Yang, W.M.[Wen-Ming],
Du, S.[Shan],
Tian, X.[Xuewu],
Li, C.[Chao],
Liao, Q.M.[Qing-Min],
Ma, H.[Hui],
Dual Polarization Modality Fusion Network for Assisting Pathological
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MedImg(42), No. 1, January 2023, pp. 304-316.
IEEE DOI
2301
Cancer, Pathology, Imaging, Feature extraction, Microstructure,
Optical switches, Image classification, switched attention
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Li, H.F.[Hao-Feng],
Li, G.B.[Guan-Bin],
Han, X.G.[Xiao-Guang],
Wan, X.[Xiang],
Which Pixel to Annotate: A Label-Efficient Nuclei Segmentation
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MedImg(42), No. 4, April 2023, pp. 947-958.
IEEE DOI
2304
Image segmentation, Training, Labeling, Annotations, Histopathology,
Generative adversarial networks, Big Data, Nuclei segmentation,
generative adversarial networks
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Segmenting Glandular Biopsy Images Using the Separate Merged Objects
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2304
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Ding, M.[Meidan],
Qu, A.[Aiping],
Zhong, H.Q.[Hai-Qin],
Lai, Z.H.[Zhi-Hui],
Xiao, S.[Shuomin],
He, P.[Penghui],
An enhanced vision transformer with wavelet position embedding for
histopathological image classification,
PR(140), 2023, pp. 109532.
Elsevier DOI
2305
Histopathological image classification, Vision transformer,
Convolutional neural network, Wavelet position embedding,
External multi-head attention
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Kadirappa, R.[Ravindranath],
Subbian, D.[Deivalakshmi],
Ramasamy, P.[Pandeeswari],
Ko, S.B.[Seok-Bum],
Histopathological carcinoma classification using parallel,
cross-concatenated and grouped convolutions deep neural network,
IJIST(33), No. 3, 2023, pp. 1048-1061.
DOI Link
2305
colon adenocarcinoma, deep learning, hepatocellular carcinoma,
lung adenocarcinoma, lung squamous carcinoma
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Mahapatra, S.[Suman],
Maji, P.[Pradipta],
Truncated Normal Mixture Prior Based Deep Latent Model for Color
Normalization of Histology Images,
MedImg(42), No. 6, June 2023, pp. 1746-1757.
IEEE DOI
2306
Image color analysis, Histopathology, Data mining,
Biological system modeling, Image coding, Image analysis,
truncated normal mixture model
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Hosseini, S.M.[S. Maryam],
Sikaroudi, M.[Milad],
Babaie, M.[Morteza],
Tizhoosh, H.R.,
Proportionally Fair Hospital Collaborations in Federated Learning of
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MedImg(42), No. 7, July 2023, pp. 1982-1995.
IEEE DOI
2307
Federated learning, Hospitals, Training, Data models, Servers,
Histopathology, Optimization
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Shen, Y.Q.[Yi-Qing],
Sowmya, A.[Arcot],
Luo, Y.L.[Yu-Lin],
Liang, X.Y.[Xiao-Yao],
Shen, D.G.[Ding-Gang],
Ke, J.[Jing],
A Federated Learning System for Histopathology Image Analysis With an
Orchestral Stain-Normalization GAN,
MedImg(42), No. 7, July 2023, pp. 1969-1981.
IEEE DOI
2307
Histopathology, Training, Generators, Federated learning, Servers,
Generative adversarial networks, Cancer, Federated learning,
stain normalization
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Li, S.R.[Sheng-Rui],
Zhao, Y.N.[Yi-Ning],
Zhang, J.[Jun],
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Gao, Y.[Yue],
High-Order Correlation-Guided Slide-Level Histology Retrieval With
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PAMI(45), No. 9, September 2023, pp. 11008-11023.
IEEE DOI
2309
BibRef
Li, Z.Y.[Zhong-Yu],
Li, C.Q.[Chao-Qun],
Luo, X.D.[Xiang-De],
Zhou, Y.T.[Yi-Tian],
Zhu, J.[Jihua],
Xu, C.[Cunbao],
Yang, M.[Meng],
Wu, Y.[Yenan],
Chen, Y.F.[Yi-Feng],
Toward Source-Free Cross Tissues Histopathological Cell Segmentation
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MedImg(42), No. 9, September 2023, pp. 2666-2677.
IEEE DOI
2310
BibRef
Sayaheen, Y.O.[Yasmeen O.],
Texture-based approach to classification meningioma using pathology
images,
IJCVR(13), No. 6, 2023, pp. 677-692.
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Yu, J.H.[Jia-Hui],
Ma, T.Y.[Tian-Yu],
Chen, H.[Hang],
Lai, M.[Maode],
Ju, Z.J.[Zhao-Jie],
Xu, Y.K.[Ying-Ke],
Marrying Global-Local Spatial Context for Image Patches in
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IEEE DOI
2310
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Wang, H.X.[Hong-Xiao],
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Cheng, L.[Liang],
Juncker-Jensen, A.[Anna],
Nagy, M.L.[Máté Levente],
Lu, X.[Xin],
Zhang, X.L.[Xiang-Liang],
Chen, D.Z.[Danny Z.],
CCF-GNN: A Unified Model Aggregating Appearance, Microenvironment,
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MedImg(42), No. 11, November 2023, pp. 3179-3193.
IEEE DOI
2311
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Guo, Y.F.[Yi-Fei],
Hu, M.[Menghan],
Min, X.K.[Xiong-Kuo],
Wang, Y.[Yan],
Dai, M.[Min],
Zhai, G.T.[Guang-Tao],
Zhang, X.P.[Xiao-Ping],
Yang, X.K.[Xiao-Kang],
Blind Image Quality Assessment for Pathological Microscopic Image
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2311
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Self-Supervised Digital Histopathology Image Disentanglement for
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MedImg(42), No. 12, December 2023, pp. 3625-3638.
IEEE DOI
2312
BibRef
Ke, J.[Jing],
Liu, K.[Kai],
Sun, Y.X.[Yu-Xiang],
Xue, Y.Y.[Yu-Ying],
Huang, J.X.[Jia-Xuan],
Lu, Y.Z.[Yi-Zhou],
Dai, J.[Jun],
Chen, Y.[Yaobing],
Han, X.D.[Xiao-Dan],
Shen, Y.Q.[Yi-Qing],
Shen, D.G.[Ding-Gang],
Artifact Detection and Restoration in Histology Images With
Stain-Style and Structural Preservation,
MedImg(42), No. 12, December 2023, pp. 3487-3500.
IEEE DOI Code:
WWW Link.
2312
BibRef
Hassan, T.[Taimur],
Li, Z.[Zhu],
Javed, S.[Sajid],
Dias, J.[Jorge],
Werghi, N.[Naoufel],
Neural Graph Refinement for Robust Recognition of Nuclei Communities
in Histopathological Landscape,
IP(33), 2024, pp. 241-256.
IEEE DOI
2312
BibRef
Lagogiannis, I.[Ioannis],
Meissen, F.[Felix],
Kaissis, G.[Georgios],
Rueckert, D.[Daniel],
Unsupervised Pathology Detection: A Deep Dive Into the State of the Art,
MedImg(43), No. 1, January 2024, pp. 241-252.
IEEE DOI Code:
WWW Link.
2401
BibRef
He, K.[Keke],
Zhu, J.[Jun],
Li, L.[Limiao],
Gou, F.F.[Fang-Fang],
Wu, J.[Jia],
Two-stage coarse-to-fine method for pathological images in medical
decision-making systems,
IET-IPR(18), No. 1, 2024, pp. 175-193.
DOI Link
2401
cell recognition, computer-aided diagnosis, medical decision-making system,
pathological images, segmentation and refinement
BibRef
Rao, K.[Karishma],
Bansal, M.[Manu],
Kaur, G.[Gagandeep],
An optimal system for increasing the contrast resolution qualities of
histopathology images in the wavelet domain,
IJIST(34), No. 1, 2024, pp. e22982.
DOI Link
2401
gamma function, image enhancement, particle swarm optimization,
singular value equalization
BibRef
He, Q.M.[Qi-Ming],
Zeng, S.Q.[Si-Qi],
Ge, S.[Shuang],
Wang, Y.X.[Yan-Xia],
Ye, J.[Jing],
He, Y.H.[Yong-Hong],
Guan, T.[Tian],
Wang, Z.[Zhe],
Li, J.[Jing],
Identifying and matching 12-level multistained glomeruli via deep
learning for diagnosis of glomerular diseases,
IJIST(34), No. 2, 2024, pp. e23032.
DOI Link
2402
glomerular diseases, instance segmentation, matching algorithm,
deep learning, histopathology
BibRef
Hu, W.T.[Wen-Tao],
Cheng, L.[Lianglun],
Huang, G.[Guoheng],
Yuan, X.C.[Xiao-Chen],
Zhong, G.[Guo],
Pun, C.M.[Chi-Man],
Zhou, J.[Jian],
Cai, M.[Muyan],
Learning From Incorrectness: Active Learning With Negative
Pre-Training and Curriculum Querying for Histological Tissue
Classification,
MedImg(43), No. 2, February 2024, pp. 625-637.
IEEE DOI Code:
WWW Link.
2402
Annotations, Training, Data models, Cancer, Predictive models,
Uncertainty, Costs, Active learning, negative learning,
histological tissue classification
BibRef
Zhang, Y.M.[Yuan-Ming],
Li, Z.[Zheng],
Han, X.M.[Xiang-Min],
Ding, S.S.[Sai-Sai],
Li, J.C.[Jun-Cheng],
Wang, J.[Jun],
Ying, S.H.[Shi-Hui],
Shi, J.[Jun],
Pseudo-Data Based Self-Supervised Federated Learning for
Classification of Histopathological Images,
MedImg(43), No. 3, March 2024, pp. 902-915.
IEEE DOI
2403
Solid modeling, Data models, Training, Task analysis, Moon, Multitasking,
Hospitals, Histopathological image, Barlow twins contrastive learning
BibRef
Li, J.[Jiawen],
Cheng, J.[Junru],
Meng, L.Q.[Ling-Qin],
Yan, H.[Hui],
He, Y.H.[Yong-Hong],
Shi, H.J.[Hui-Juan],
Guan, T.[Tian],
Han, A.[Anjia],
DeepTree: Pathological Image Classification Through Imitating
Tree-Like Strategies of Pathologists,
MedImg(43), No. 4, April 2024, pp. 1501-1512.
IEEE DOI
2404
Pathology, Morphology, Tumors, Lesions, Feature extraction,
Deep learning, Image classification, Deep learning,
tree-like strategies
BibRef
Zhong, L.F.[Lan-Feng],
Luo, X.D.[Xiang-De],
Liao, X.[Xin],
Zhang, S.T.[Shao-Ting],
Wang, G.[Guotai],
Semi-supervised pathological image segmentation via cross
distillation of multiple attentions and Seg-CAM consistency,
PR(152), 2024, pp. 110492.
Elsevier DOI Code:
WWW Link.
2405
Semi-supervised learning, Knowledge distillation, Attention, Multi-task learning
BibRef
Vray, G.[Guillaume],
Tomar, D.[Devavrat],
Bozorgtabar, B.[Behzad],
Thiran, J.P.[Jean-Philippe],
Distill-SODA: Distilling Self-Supervised Vision Transformer for
Source-Free Open-Set Domain Adaptation in Computational Pathology,
MedImg(43), No. 5, May 2024, pp. 2021-2032.
IEEE DOI
2405
Adaptation models, Transformers, Prototypes, Training, Task analysis,
Semantics, Histopathology, Histopathological image analysis,
self-supervised vision transformer
BibRef
Ahmad, I.[Ibtihaj],
Israr, S.M.[Syed Muhammad],
Islam, Z.U.[Zain Ul],
A three in one bottom-up framework for simultaneous semantic
segmentation, instance segmentation and classification of multi-organ
nuclei in digital cancer histology,
IVC(146), 2024, pp. 105047.
Elsevier DOI
2405
Nuclei segmentation, Nuclei classification,
Simultaneous segmentation and classification,
Tumor segmentation and classification
BibRef
Gour, M.[Mahesh],
Jain, S.[Sweta],
Kumar, T. .S.I.[T. Sun-Il],
Robust nuclei segmentation with encoder-decoder network from the
histopathological images,
IJIST(34), No. 4, 2024, pp. e23111.
DOI Link
2406
encoder-decoder network, multi-organ histopathological images,
nuclei segmentation, post-processing, pre-trained EfficientNet
BibRef
Yun, B.X.[Bo-Xiang],
Lei, B.Y.[Bai-Ying],
Chen, J.[Jieneng],
Wang, H.Y.[Hui-Yu],
Qiu, S.[Song],
Shen, W.[Wei],
Li, Q.L.[Qing-Li],
Wang, Y.[Yan],
SpecTr: Spectral Transformer for Microscopic Hyperspectral Pathology
Image Segmentation,
CirSysVideo(34), No. 6, June 2024, pp. 4610-4624.
IEEE DOI Code:
WWW Link.
2406
Pathology, Image segmentation, Hyperspectral imaging, Feature extraction,
Transformers, Microscopy, Biomedical imaging, microscopy
BibRef
Shao, W.[Wei],
Shi, H.[Hang],
Liu, J.X.[Jian-Xin],
Zuo, Y.L.[Ying-Li],
Sun, L.[Liang],
Xia, T.[Tiansong],
Chen, W.[Wanyuan],
Wan, P.[Peng],
Sheng, J.P.[Jian-Peng],
Zhu, Q.[Qi],
Zhang, D.Q.[Dao-Qiang],
Multi-Instance Multi-Task Learning for Joint Clinical Outcome and
Genomic Profile Predictions From the Histopathological Images,
MedImg(43), No. 6, June 2024, pp. 2266-2278.
IEEE DOI
2406
Task analysis, Cancer, Multitasking,
Prognostics and health management, Predictive models, Genomics, deep learning
BibRef
Wang, H.[Hao],
Ahn, E.[Euijoon],
Kim, J.M.[Jin-Man],
A multi-resolution self-supervised learning framework for semantic
segmentation in histopathology,
PR(155), 2024, pp. 110621.
Elsevier DOI
2408
Multi-resolution histopathology learning,
Self-supervised learning, Semantic segmentation
BibRef
Guan, X.[Xi],
Zhu, Q.[Qi],
Sun, L.[Liang],
Zhao, J.Y.[Jun-Yong],
Zhang, D.Q.[Dao-Qiang],
Wan, P.[Peng],
Shao, W.[Wei],
Global-local consistent semi-supervised segmentation of
histopathological image with different perturbations,
PR(155), 2024, pp. 110696.
Elsevier DOI Code:
WWW Link.
2408
Pathological image, Semi-supervised segmentation,
Generative adversarial learning, Global-local consistent
BibRef
Wen, Z.J.[Zhi-Jie],
Wu, H.X.[Hai-Xia],
Ying, S.H.[Shi-Hui],
Histopathology Image Classification With Noisy Labels via The Ranking
Margins,
MedImg(43), No. 8, August 2024, pp. 2790-2802.
IEEE DOI
2408
Training, Noise measurement, Histopathology,
Transmission line measurements, Annotations, Tuning, Skin,
the ranking margins
BibRef
Liu, M.X.[Ming-Xin],
Liu, Y.Z.[Yun-Zan],
Xu, P.[Pengbo],
Cui, H.[Hui],
Ke, J.[Jing],
Ma, J.[Jiquan],
Exploiting Geometric Features via Hierarchical Graph Pyramid
Transformer for Cancer Diagnosis Using Histopathological Images,
MedImg(43), No. 8, August 2024, pp. 2888-2900.
IEEE DOI
2408
Cancer, Transformers, Image classification, Histopathology,
Computer architecture, Deep learning, Feature extraction,
geometric feature representation
BibRef
He, Y.F.[Yu-Fang],
Liu, Z.[Zeyu],
Qi, M.X.[Ming-Xin],
Ding, S.W.[Sheng-Wei],
Zhang, P.[Peng],
Song, F.[Fan],
Ma, C.[Chenbin],
Wu, H.J.[Hui-Jie],
Cai, R.[Ruxin],
Feng, Y.[Youdan],
Zhang, H.[Haonan],
Zhang, T.Y.[Tian-Yi],
Zhang, G.L.[Guang-Lei],
PST-Diff: Achieving High-Consistency Stain Transfer by Diffusion
Models With Pathological and Structural Constraints,
MedImg(43), No. 10, October 2024, pp. 3634-3647.
IEEE DOI
2411
Pathology, Diffusion models, Cancer, Accuracy,
Active appearance model, Task analysis, Image synthesis,
hematoxylin and eosin (HE)
BibRef
Han, J.X.[Jiang-Xiao],
Wang, S.K.[Shi-Kang],
Deng, X.B.[Xian-Bo],
Liu, W.Y.[Wen-Yu],
High-performance mitosis detection using single-level feature and
hybrid label assignment,
IVC(151), 2024, pp. 105291.
Elsevier DOI
2411
Mitosis detection, Medical image analysis, Histopathology,
Hybrid label assignment, Bipartite matching
BibRef
Shi, S.Z.[Sheng-Zhe],
Wang, Y.Y.[Yan-Yan],
Zhang, K.[Kaikai],
Wang, Q.Q.[Qing-Qing],
Liu, S.[Sheng],
Wang, C.[Chun],
Palette-based colour normalization for histopathology images,
IET-IPR(18), No. 13, 2024, pp. 4368-4380.
DOI Link
2411
biomedical imaging, image processing, medical image processing
BibRef
Tang, W.H.[Wen-Hao],
Zhou, F.T.[Feng-Tao],
Huang, S.[Sheng],
Zhu, X.[Xiang],
Zhang, Y.[Yi],
Liu, B.[Bo],
Feature Re-Embedding: Towards Foundation Model-Level Performance in
Computational Pathology,
CVPR24(11343-11352)
IEEE DOI Code:
WWW Link.
2410
Pathology, Limiting, Codes, Computational modeling,
Computer architecture, Feature extraction, Representation Learning
BibRef
Yin, C.[Chong],
Liu, S.Q.[Si-Qi],
Zhou, K.Y.[Kai-Yang],
Wong, V.W.S.[Vincent Wai-Sun],
Yuen, P.C.[Pong C.],
Prompting Vision Foundation Models for Pathology Image Analysis,
CVPR24(11292-11301)
IEEE DOI Code:
WWW Link.
2410
Pathology, Visualization, Image analysis, Image recognition, Data analysis,
Liver diseases, Prompt, pathology image analysis, quantitative attributes
BibRef
Phan, V.M.H.[Vu Minh Hieu],
Xie, Y.T.[Yu-Tong],
Qi, Y.[Yuankai],
Liu, L.Q.[Ling-Qiao],
Liu, L.Y.[Li-Yang],
Zhang, B.[Bowen],
Liao, Z.B.[Zhi-Bin],
Wu, Q.[Qi],
To, M.S.[Minh-Son],
Verjans, J.W.[Johan W.],
Decomposing Disease Descriptions for Enhanced Pathology Detection: A
Multi-Aspect Vision-Language Pre-Training Framework,
CVPR24(11492-11501)
IEEE DOI Code:
WWW Link.
2410
Pathology, Visualization, Large language models, Semantics,
Performance gain, Image representation, Transformers,
Visual grounding
BibRef
Seyfioglu, M.S.[Mehmet Saygin],
Ikezogwo, W.O.[Wisdom O.],
Ghezloo, F.[Fatemeh],
Krishna, R.[Ranjay],
Shapiro, L.[Linda],
Quilt-LLaVA: Visual Instruction Tuning by Extracting Localized
Narratives from Open-Source Histopathology Videos,
CVPR24(13183-13192)
IEEE DOI
2410
Training, Visualization, Video on demand, Histopathology, Cognition,
Question answering (information retrieval), Medical
BibRef
Alfasly, S.[Saghir],
Shafique, A.[Abubakr],
Nejat, P.[Peyman],
Khan, J.[Jibran],
Alsaafin, A.[Areej],
Alabtah, G.[Ghazal],
Tizhoosh, H.R.,
Rotation-Agnostic Image Representation Learning for Digital Pathology,
CVPR24(11683-11693)
IEEE DOI Code:
WWW Link.
2410
Training, Representation learning, Pathology, Image analysis,
Accuracy, Morphology, Self-supervised learning, Histopathology,
WSI
BibRef
Jaume, G.[Guillaume],
Vaidya, A.[Anurag],
Chen, R.J.[Richard J.],
Williamson, D.F.K.[Drew F.K.],
Liang, P.P.[Paul Pu],
Mahmood, F.[Faisal],
Modeling Dense Multimodal Interactions Between Biological Pathways
and Histology for Survival Prediction,
CVPR24(11579-11590)
IEEE DOI Code:
WWW Link.
2410
Histopathology, Computational modeling,
Biological system modeling, Transcriptomics, Predictive models,
biomarker discovery
BibRef
Javed, S.[Sajid],
Mahmood, A.[Arif],
Ganapathi, I.I.[Iyyakutti Iyappan],
Dharejo, F.A.[Fayaz Ali],
Werghi, N.[Naoufel],
Bennamoun, M.[Mohammed],
CPLIP: Zero-Shot Learning for Histopathology with Comprehensive
Vision-Language Alignment,
CVPR24(11450-11459)
IEEE DOI Code:
WWW Link.
2410
Visualization, Image segmentation, Zero-shot learning,
Histopathology, Computational modeling, Contrastive learning,
Contrastive Loss
BibRef
Wang, H.[Huyong],
Wu, H.[Huisi],
Qin, J.[Jing],
Incremental Nuclei Segmentation from Histopathological Images via
Future-class Awareness and Compatibility-inspired Distillation,
CVPR24(11408-11417)
IEEE DOI Code:
WWW Link.
2410
Training, Codes, Computational modeling, Semantic segmentation,
Software
BibRef
Li, J.[Jiahan],
Dong, J.[Jiuyang],
Huang, S.[Shenjin],
Li, X.[Xi],
Jiang, J.J.[Jun-Jun],
Fan, X.P.[Xiao-Peng],
Zhang, Y.B.[Yong-Bing],
Virtual Immunohistochemistry Staining for Histological Images
Assisted by Weakly-supervised Learning,
CVPR24(11259-11268)
IEEE DOI Code:
WWW Link.
2410
Training, Visualization, Accuracy, Codes, Image synthesis,
Histopathology, Virtual Immunohistochemistry Staining, High-resolution
BibRef
Kapse, S.[Saarthak],
Pati, P.[Pushpak],
Das, S.[Srijan],
Zhang, J.W.[Jing-Wei],
Chen, C.[Chao],
Vakalopoulou, M.[Maria],
Saltz, J.[Joel],
Samaras, D.[Dimitris],
Gupta, R.R.[Rajarsi R.],
Prasanna, P.[Prateek],
SI-MIL: Taming Deep MIL for Self-Interpretability in Gigapixel
Histopathology,
CVPR24(11226-11237)
IEEE DOI
2410
Training, Histopathology, Statistical analysis,
Computational modeling, Predictive models, Cognition, Histopathology
BibRef
Graikos, A.[Alexandros],
Yellapragada, S.[Srikar],
Le, M.Q.[Minh-Quan],
Kapse, S.[Saarthak],
Prasanna, P.[Prateek],
Saltz, J.[Joel],
Samaras, D.[Dimitris],
Learned Representation-Guided Diffusion Models for Large-Image
Generation,
CVPR24(8532-8542)
IEEE DOI
2410
Training, Adaptation models, Visualization, Image synthesis,
Histopathology, Annotations, Computational modeling, generative models
BibRef
Guichemerre, A.[Alexis],
Belharbi, S.[Soufiane],
Mayet, T.[Tsiry],
Murtaza, S.[Shakeeb],
Shamsolmoali, P.[Pourya],
McCaffrey, L.[Luke],
Granger, E.[Eric],
Source-Free Domain Adaptation of Weakly-Supervised Object
Localization Models for Histology,
UG24(33-43)
IEEE DOI
2410
Location awareness, Deep learning, Adaptation models, Data privacy,
Histopathology, Estimation, Contrastive learning
BibRef
Mota, T.[Tiago],
Verdelho, M.R.[M. Rita],
Araújo, D.J.[Diogo J.],
Bissoto, A.[Alceu],
Santiago, C.[Carlos],
Barata, C.[Catarina],
MMIST-ccRCC: A Real World Medical Dataset for the Development of
Multi-Modal Systems,
EnhanceMedIm24(2395-2403)
IEEE DOI
2410
Histopathology, Magnetic resonance imaging, Genomics, Proteomics,
Medical services, Radiology, Benchmark testing
BibRef
Wood, R.[Ruby],
Domingo, E.[Enric],
Koelzer, V.H.[Viktor Hendrik],
Maughan, T.S.[Timothy S.],
Rittscher, J.[Jens],
Cluster Triplet Loss for Unsupervised Domain Adaptation on Histology
Images,
DEF-AI-MIA24(5122-5131)
IEEE DOI
2410
Deep learning, Adaptation models, Histopathology,
Biological system modeling, Noise, Predictive models,
histology
BibRef
Nasiri-Sarvi, A.[Ali],
Trinh, V.Q.H.[Vincent Quoc-Huy],
Rivaz, H.[Hassan],
Hosseini, M.S.[Mahdi S.],
Vim4Path: Self-Supervised Vision Mamba for Histopathology Images,
CVMI24(6894-6903)
IEEE DOI Code:
WWW Link.
2410
Representation learning, Training, Adaptation models,
Computational modeling, Self-supervised learning, Cancer Diagnosis
BibRef
Ignatov, A.[Andrey],
Yates, J.[Josephine],
Boeva, V.[Valentina],
Histopathological Image Classification with Cell Morphology Aware
Deep Neural Networks,
CVMI24(6913-6925)
IEEE DOI Code:
WWW Link.
2410
Image segmentation, Analytical models, Accuracy, Microscopy,
Microprocessors, Computational modeling, Deep Learning, Cell Morphology
BibRef
Song, A.H.[Andrew H.],
Chen, R.J.[Richard J.],
Ding, T.[Tong],
Williamson, D.F.K.[Drew F.K.],
Jaume, G.[Guillaume],
Mahmood, F.[Faisal],
Morphological Prototyping for Unsupervised Slide Representation
Learning in Computational Pathology,
CVPR24(11566-11578)
IEEE DOI Code:
WWW Link.
2410
Representation learning, Pathology, Analytical models, Codes,
Computational modeling, Redundancy, computational pathology,
set representation learning
BibRef
Jaume, G.[Guillaume],
Oldenburg, L.[Lukas],
Vaidya, A.[Anurag],
Chen, R.J.[Richard J.],
Williamson, D.F.K.[Drew F.K.],
Peeters, T.[Thomas],
Song, A.H.[Andrew H.],
Mahmood, F.[Faisal],
Transcriptomics-Guided Slide Representation Learning in Computational
Pathology,
CVPR24(9632-9644)
IEEE DOI Code:
WWW Link.
2410
Representation learning, Training, Histopathology, Lung, Liver,
Contrastive learning, Breast, slide representation learning,
computational pathology
BibRef
Yang, Y.[Yan],
Pan, L.Y.[Li-Yuan],
Liu, L.[Liu],
Stone, E.A.[Eric A.],
Convolutional Masked Image Modeling for Dense Prediction Tasks on
Pathology Images,
WACV24(7783-7793)
IEEE DOI
2404
Pathology, Image coding, Shape, Image color analysis,
Transfer learning, Glands, Predictive models, Applications,
Biomedical / healthcare / medicine
BibRef
Yellapragada, S.[Srikar],
Graikos, A.[Alexandros],
Prasanna, P.[Prateek],
Kurc, T.[Tahsin],
Saltz, J.[Joel],
Samaras, D.[Dimitris],
PathLDM: Text conditioned Latent Diffusion Model for Histopathology,
WACV24(5170-5179)
IEEE DOI
2404
Training, Visualization, Histopathology, Fuses,
Computational modeling, Buildings, Algorithms,
Biomedical / healthcare / medicine
BibRef
Nakhli, R.[Ramin],
Zhang, A.[Allen],
Mirabadi, A.[Ali],
Rich, K.[Katherine],
Asadi, M.[Maryam],
Gilks, B.[Blake],
Farahani, H.[Hossein],
Bashashati, A.[Ali],
CO-PILOT: Dynamic Top-Down Point Cloud with Conditional Neighborhood
Aggregation for Multi-Gigapixel Histopathology Image Representation,
ICCV23(21006-21016)
IEEE DOI
2401
BibRef
Jiménez, L.G.[Laura Gálvez],
Dierckx, L.[Lucile],
Amodei, M.[Maxime],
Khosroshahi, H.R.[Hamed Razavi],
Chidambaran, N.[Natarajan],
Ho, A.T.P.[Anh-Thu Phan],
Franzin, A.[Alberto],
Computational Evaluation of the Combination of Semi-Supervised and
Active Learning for Histopathology Image Segmentation with Missing
Annotations,
CVAMD23(2544-2555)
IEEE DOI
2401
BibRef
Sikaroudi, M.[Milad],
Hosseini, M.[Maryam],
Rahnamayan, S.[Shahryar],
Tizhoosh, H.R.,
ALFA: Leveraging All Levels of Feature Abstraction for Enhancing the
Generalization of Histopathology Image Classification Across Unseen
Hospitals,
CVAMD23(2656-2665)
IEEE DOI Code:
WWW Link.
2401
BibRef
Wu, W.Y.[Wei-Yi],
Gao, C.Y.[Chong-Yang],
DiPalma, J.[Joseph],
Vosoughi, S.[Soroush],
Hassanpour, S.[Saeed],
Improving Representation Learning for Histopathologic Images with
Cluster Constraints,
ICCV23(21347-21357)
IEEE DOI Code:
WWW Link.
2401
BibRef
Lee, J.C.[Ju Cheon],
Kwak, J.T.[Jin Tae],
Order-ViT: Order Learning Vision Transformer for Cancer
Classification in Pathology Images,
CVAMD23(2485-2494)
IEEE DOI
2401
BibRef
Lai, Z.F.[Zheng-Feng],
Li, Z.H.[Zhuo-Heng],
Oliveira, L.C.[Luca Cerny],
Chauhan, J.[Joohi],
Dugger, B.N.[Brittany N.],
Chuah, C.N.[Chen-Nee],
CLIPath: Fine-tune CLIP with Visual Feature Fusion for Pathology
Image Analysis Towards Minimizing Data Collection Efforts,
CVAMD23(2366-2372)
IEEE DOI
2401
BibRef
Ryu, J.[Jeongun],
Puche, A.V.[Aaron Valero],
Shin, J.W.[Jae-Woong],
Park, S.[Seonwook],
Brattoli, B.[Biagio],
Lee, J.[Jinhee],
Jung, W.[Wonkyung],
Cho, S.I.[Soo Ick],
Paeng, K.[Kyunghyun],
Ock, C.Y.[Chan-Young],
Yoo, D.[Donggeun],
Pereira, S.[Sérgio],
OCELOT: Overlapped Cell on Tissue Dataset for Histopathology,
CVPR23(23902-23912)
IEEE DOI
2309
BibRef
Zedda, L.[Luca],
Loddo, A.[Andrea],
di Ruberto, C.[Cecilia],
Hierarchical Pretrained Backbone Vision Transformer for Image
Classification in Histopathology,
CIAP23(II:223-234).
Springer DOI
2312
BibRef
Bontempo, G.[Gianpaolo],
Bartolini, N.[Nicola],
Lovino, M.[Marta],
Bolelli, F.[Federico],
Virtanen, A.[Anni],
Ficarra, E.[Elisa],
Enhancing PFI Prediction with GDS-MIL:
A Graph-based Dual Stream MIL Approach,
CIAP23(I:550-562).
Springer DOI
2312
BibRef
Nau, A.M.[Anna-Maria],
Mockus, A.[Audris],
Steadman, D.W.[Dawnie Wolfe],
Stage of Decay Estimation Exploiting Exogenous and Endogenous Image
Attributes to Minimize Manual Labeling Efforts and Maximize
Classification Performance,
ICIP23(2705-2709)
IEEE DOI
2312
For human remains.
BibRef
Long, X.[Xi],
Liu, J.X.[Jing-Xin],
Hou, X.X.[Xian-Xu],
Domain Adaptation of Digital Pathology Images using Joint Stain Color
and Image Quality Constraints,
ICIP23(1805-1809)
IEEE DOI
2312
BibRef
Tan, C.H.[Choo Hui],
Lim, W.J.[Wei Jie],
Ahmad, W.S.H.M.W.[Wan Siti Halimatul Munirah Wan],
Wong, L.K.[Lai-Kuan],
Rehman, Z.U.[Zaka Ur],
Looi, L.M.[Lai Meng],
Cheah, P.L.[Phaik Leng],
Toh, Y.F.[Yen Fa],
Fauzi, M.F.A.[Mohammad Faizal Ahmad],
HER2-Sish Histopathology Image Classification Using Deep Neural
Networks,
ICIP23(2500-2504)
IEEE DOI
2312
BibRef
Sun, K.X.[Ke-Xin],
Chen, Z.N.[Zhi-Neng],
Wang, G.W.[Gong-Wei],
Liu, J.[Jun],
Ye, X.J.[Xiong-Jun],
Jiang, Y.G.[Yu-Gang],
Bi-directional Feature Fusion Generative Adversarial Network for
Ultra-high Resolution Pathological Image Virtual Re-Staining,
CVPR23(3904-3913)
IEEE DOI
2309
BibRef
Kang, M.[Mingu],
Song, H.[Heon],
Park, S.[Seonwook],
Yoo, D.G.[Dong-Geun],
Pereira, S.[Sérgio],
Benchmarking Self-Supervised Learning on Diverse Pathology Datasets,
CVPR23(3344-3354)
IEEE DOI
2309
BibRef
Lu, M.Y.[Ming Y.],
Chen, B.[Bowen],
Zhang, A.[Andrew],
Williamson, D.F.K.[Drew F.K.],
Chen, R.J.[Richard J.],
Ding, T.[Tong],
Le, L.P.[Long Phi],
Chuang, Y.S.[Yung-Sung],
Mahmood, F.[Faisal],
Visual Language Pretrained Multiple Instance Zero-Shot Transfer for
Histopathology Images,
CVPR23(19764-19775)
IEEE DOI
2309
BibRef
Qin, W.K.[Wen-Kang],
Xu, R.[Rui],
Jiang, S.[Shan],
Jiang, T.T.[Ting-Ting],
Luo, L.[Lin],
Pathtr: Context-aware Memory Transformer for Tumor Localization in
Gigapixel Pathology Images,
ACCV22(VI:115-131).
Springer DOI
2307
BibRef
Wang, Q.[Qian],
Chen, Z.[Zhao],
A Deep Wavelet Network for High-resolution Microscopy Hyperspectral
Image Reconstruction,
MIA-COVID19D22(648-662).
Springer DOI
2304
BibRef
Singh, P.[Pranav],
Cirrone, J.[Jacopo],
A Data-efficient Deep Learning Framework for Segmentation and
Classification of Histopathology Images,
MCV22(385-405).
Springer DOI
2304
BibRef
Wibawa, M.S.[Made Satria],
Lo, K.W.[Kwok-Wai],
Young, L.S.[Lawrence S.],
Rajpoot, N.[Nasir],
Multi-scale Attention-based Multiple Instance Learning for
Classification of Multi-gigapixel Histology Images,
MIA-COVID19D22(635-647).
Springer DOI
2304
BibRef
Mormont, R.[Romain],
Testouri, M.[Mehdi],
Marée, R.[Raphaël],
Geurts, P.[Pierre],
Relieving Pixel-wise Labeling Effort for Pathology Image Segmentation
with Self-training,
MIA-COVID19D22(577-592).
Springer DOI
2304
BibRef
Kang, C.M.[Chol-Min],
Lee, C.G.[Chung-Gi],
Song, H.[Heon],
Ma, M.[Minuk],
Pereira, S.[Sérgio],
Variability Matters: Evaluating Inter-rater Variability in
Histopathology for Robust Cell Detection,
MIA-COVID19D22(552-565).
Springer DOI
2304
BibRef
Wölflein, G.[Georg],
Um, I.H.[In Hwa],
Harrison, D.J.[David J.],
Arandjelovic, O.[Ognjen],
HoechstGAN: Virtual Lymphocyte Staining Using Generative Adversarial
Networks,
WACV23(4986-4996)
IEEE DOI
2302
Measurement, Generative adversarial networks, Task analysis,
Signal to noise ratio, Cancer.
BibRef
Stegmüller, T.[Thomas],
Bozorgtabar, B.[Behzad],
Spahr, A.[Antoine],
Thiran, J.P.[Jean-Philippe],
ScoreNet: Learning Non-Uniform Attention and Augmentation for
Transformer-Based Histopathological Image Classification,
WACV23(6159-6168)
IEEE DOI
2302
Costs, Histopathology, Semantics, Transformers, Throughput,
Applications: Biomedical/healthcare/medicine
BibRef
Liu, K.[Kechun],
Li, B.[Beibin],
Wu, W.J.[Wen-Jun],
May, C.[Caitlin],
Chang, O.[Oliver],
Knezevich, S.[Stevan],
Reisch, L.[Lisa],
Elmore, J.[Joann],
Shapiro, L.[Linda],
VSGD-Net: Virtual Staining Guided Melanocyte Detection on
Histopathological Images,
WACV23(1918-1927)
IEEE DOI
2302
Visualization, Pathology, Image synthesis,
Biological system modeling, Source coding, Biopsy, Melanoma,
visual reasoning
BibRef
Moghadam, P.A.[Puria Azadi],
van Dalen, S.[Sanne],
Martin, K.C.[Karina C.],
Lennerz, J.[Jochen],
Yip, S.[Stephen],
Farahani, H.[Hossein],
Bashashati, A.[Ali],
A Morphology Focused Diffusion Probabilistic Model for Synthesis of
Histopathology Images,
WACV23(1999-2008)
IEEE DOI
2302
Visualization, Histopathology, Image color analysis,
Computational modeling, Microscopy, Morphology, Brain modeling,
Applications: Biomedical/healthcare/medicine
BibRef
Guan, R.W.[Run-Wei],
Fei, Y.H.[Yan-Hua],
Zhu, X.H.[Xiao-Hui],
Yao, S.L.[Shan-Liang],
Yue, Y.[Yong],
Ma, J.M.[Jie-Ming],
CPNet: A Hybrid Neural Network for Identification of Carcinoma
Pathological Slices,
ICIVC22(599-604)
IEEE DOI
2301
Training, Deep learning, Pathology, Costs, Codes, Computational modeling,
Transfer learning, intelligent medicine, CNN-ViT hybrid NN
BibRef
Teh, E.W.[Eu Wern],
Taylor, G.W.[Graham W.],
Understanding the impact of image and input resolution on deep
digital pathology patch classifiers,
CRV22(159-166)
IEEE DOI
2301
Pathology, Image resolution, Correlation, Annotations, Data models, Tuning,
Robots, Digital Pathology, Patch Classification, Annotation-efficient Learning
BibRef
Li, M.[Meng],
Li, C.Y.[Chao-Yi],
Hobson, P.[Peter],
Jennings, T.[Tony],
Lovell, B.C.[Brian C.],
MedViTGAN: End-to-End Conditional GAN for Histopathology Image
Augmentation with Vision Transformers,
ICPR22(4406-4413)
IEEE DOI
2212
Training, Adaptation models, Histopathology, Image synthesis,
Semantic segmentation, Computer architecture, Transformers, Vision transformer
BibRef
Alhammad, S.[Sarah],
Zhang, T.[Teng],
Zhao, K.[Kun],
Hobson, P.[Peter],
Jennings, A.[Anthony],
Lovell, B.C.[Brian C.],
Efficient Cell Labelling for Gram Stain WSIs,
ICPR22(4226-4233)
IEEE DOI
2212
Training, Pathology, Annotations, Scholarships, Manuals, Detectors,
Transformers, WSI, Gram Stain Analysis, Detection, CNN, Cell Counting,
Microbiology
BibRef
Si, Y.X.[Yu-Xuan],
Fang, Z.Q.[Zheng-Qing],
Kuang, K.[Kun],
Huang, Z.X.[Zheng-Xing],
Yao, Y.F.[Yu-Feng],
Wu, F.[Fei],
Disentangled Sequential Autoencoder with Local Consistency for
Infectious Keratitis Diagnosis,
ICIP22(3893-3897)
IEEE DOI
2211
Deep learning, Pathology, Pathogens, Shape, Visual impairment,
Time series analysis, Inference algorithms,
Infectious Keratitis
BibRef
Lotfollahi, M.[Mahsa],
Tran, N.[Nguyen],
Gajjela, C.[Chalapathi],
Berisha, S.[Sebastian],
Han, Z.[Zhu],
Mayerich, D.[David],
Reddy, R.[Rohith],
Adaptive Compressive Sampling for Mid-Infrared Spectroscopic Imaging,
ICIP22(2336-2340)
IEEE DOI
2211
Measurement, Tensors, Image coding, Image synthesis, Histopathology,
Training data, Spatial resolution, Adaptive Sampling,
SVM Classification Metric
BibRef
Dwivedi, C.[Chaitanya],
Nofallah, S.[Shima],
Pouryahya, M.[Maryam],
Iyer, J.[Janani],
Leidal, K.[Kenneth],
Chung, C.H.[Chu-Han],
Watkins, T.[Timothy],
Billin, A.[Andrew],
Myers, R.[Robert],
Abel, J.[John],
Behrooz, A.[Ali],
Multi stain graph fusion for multimodal integration in pathology,
CVMI22(1834-1844)
IEEE DOI
2210
Weight measurement, Histopathology, Computational modeling,
Conferences, Liver, Predictive models
BibRef
Alali, M.H.[Mohammed H.],
Roohi, A.[Arman],
Deogun, J.S.[Jitender S.],
Enabling Efficient Training of Convolutional Neural Networks for
Histopathology Images,
DeepHealth22(533-544).
Springer DOI
2208
BibRef
Gräbel, P.[Philipp],
Thull, J.[Julian],
Crysandt, M.[Martina],
Klinkhammer, B.M.[Barbara M.],
Boor, P.[Peter],
Brümmendorf, T.H.[Tim H.],
Merhof, D.[Dorit],
Spatial Maturity Regression for the Classification of Hematopoietic
Cells,
IPTA22(1-6)
IEEE DOI
2206
Visualization, Microscopy, Image processing, Neural networks,
Cells (biology), Bones, Blood, representation learning,
em-bedding guides
BibRef
Azizi, S.[Shekoofeh],
Mustafa, B.[Basil],
Ryan, F.[Fiona],
Beaver, Z.[Zachary],
Freyberg, J.[Jan],
Deaton, J.[Jonathan],
Loh, A.[Aaron],
Karthikesalingam, A.[Alan],
Kornblith, S.[Simon],
Chen, T.[Ting],
Natarajan, V.[Vivek],
Norouzi, M.[Mohammad],
Big Self-Supervised Models Advance Medical Image Classification,
ICCV21(3458-3468)
IEEE DOI
2203
Pathology, Image recognition, Annotations, Dermatology,
Digital cameras, Task analysis, Medical, biological,
BibRef
Abousamra, S.[Shahira],
Belinsky, D.[David],
van Arnam, J.[John],
Allard, F.[Felicia],
Yee, E.[Eric],
Gupta, R.[Rajarsi],
Kurc, T.[Tahsin],
Samaras, D.[Dimitris],
Saltz, J.[Joel],
Chen, C.[Chao],
Multi-Class Cell Detection Using Spatial Context Representation,
ICCV21(3985-3994)
IEEE DOI
2203
Representation learning, Multiplexing, Pathology,
Clustering methods, Topology, Task analysis, Medical, biological,
BibRef
Wang, H.T.[Hao-Tian],
Xian, M.[Min],
Vakanski, A.[Aleksandar],
TA-Net: Topology-Aware Network for Gland Segmentation,
WACV22(3241-3249)
IEEE DOI
2202
Image segmentation, Network topology, Histopathology, Semantics,
Glands, Morphology, Computer architecture, Grouping and Shape
BibRef
Sahel, Y.B.[Yair Ben],
Dardikman-Yoffe, G.[Gilli],
Eldar, Y.C.[Yonina C.],
Gosh, S.[Shirsendu],
Haran, G.[Gilad],
Super-Resolved Imaging of Early-Stage Dynamics in the Immune Response,
ICIP21(3468-3472)
IEEE DOI
2201
Location awareness, Surface reconstruction, Diffraction,
Microscopy, Superresolution, Real-time systems, Surface topography,
High-Resolution Imaging
BibRef
Shen, Y.Q.[Yi-Qing],
Ke, J.[Jing],
Su-Sampling Based Active Learning for Large-Scale Histopathology
Image,
ICIP21(116-120)
IEEE DOI
2201
Deep learning, Image segmentation, Uncertainty,
Monte Carlo methods, Annotations, Histopathology, Neural networks,
convolutional neural network
BibRef
Li, M.[Meng],
Zhao, K.[Kun],
Peng, C.[Can],
Hobson, P.[Peter],
Jennings, T.[Tony],
Lovell, B.C.[Brian C.],
Deep Adaptive Few Example Learning for Microscopy Image Cell Counting,
DICTA21(1-7)
IEEE DOI
2201
Training, Deep learning, Adaptation models, Adaptive systems,
Histopathology, Microscopy, Digital images,
Few-shot Learning
BibRef
Dodballapur, V.[Veena],
Song, Y.[Yang],
Huang, H.[Heng],
Chen, M.[Mei],
Chrzanowski, W.[Wojciech],
Cai, W.D.[Wei-Dong],
Dual-Stage Domain Adaptive Mitosis Detection for Histopathology
Images,
DICTA20(1-7)
IEEE DOI
2201
Training, Adaptive systems, Histopathology, Neural networks,
Pipelines, Machine learning, Testing, Domain adaptation, mitosis,
convolutional neural networks
BibRef
Gräbel, P.[Philipp],
Crysandt, M.[Martina],
Klinkhammer, B.M.[Barbara M.],
Boor, P.[Peter],
Brümmendorf, T.H.[Tim H.],
Merhof, D.[Dorit],
Guided Representation Learning for the Classification of
Hematopoietic Cells,
CDPath21(545-551)
IEEE DOI
2112
Training, Dimensionality reduction, Image analysis, Microscopy,
Knowledge based systems, Throughput
BibRef
Pahwa, E.[Esha],
Mehta, D.[Dwij],
Kapadia, S.[Sanjeet],
Jain, D.[Devansh],
Luthra, A.[Achleshwar],
MedSkip: Medical Report Generation Using Skip Connections and
Integrated Attention,
CVAMD21(3402-3408)
IEEE DOI
2112
Visualization, Pathology, Computer architecture,
Radiology, Transformers, Feature extraction
BibRef
Dawood, M.[Muhammad],
Branson, K.[Kim],
Rajpoot, N.M.[Nasir M.],
Minhas, F.U.A.A.[Fayyaz Ul Amir Afsar],
ALBRT: Cellular Composition Prediction in Routine Histology Images,
CDPath21(664-673)
IEEE DOI
2112
Codes, Histopathology, Topology, Task analysis, Tumors
BibRef
Jahanifar, M.[Mostafa],
Tajeddin, N.Z.[Neda Zamani],
Koohbanani, N.A.[Navid Alemi],
Rajpoot, N.[Nasir],
Robust Interactive Semantic Segmentation of Pathology Images with
Minimal User Input,
CDPath21(674-683)
IEEE DOI
2112
Geometry, Deep learning, Image segmentation, Histopathology,
Annotations, Computational modeling, Semantics
BibRef
Jewsbury, R.[Robert],
Bhalerao, A.[Abhir],
Rajpoot, N.[Nasir],
A QuadTree Image Representation for Computational Pathology,
CDPath21(648-656)
IEEE DOI
2112
Visualization, Histopathology, Pipelines,
Data visualization, Image representation, Prediction algorithms
BibRef
Boyd, J.[Joseph],
Liashuha, M.[Mykola],
Deutsch, E.[Eric],
Paragios, N.[Nikos],
Christodoulidis, S.[Stergios],
Vakalopoulou, M.[Maria],
Self-Supervised Representation Learning using Visual Field Expansion
on Digital Pathology,
CDPath21(639-647)
IEEE DOI
2112
Visualization, Codes, Histopathology,
Computational modeling, Tools
BibRef
Lai, Z.F.[Zheng-Feng],
Wang, C.[Chao],
Oliveira, L.C.[Luca Cerny],
Dugger, B.N.[Brittany N.],
Cheung, S.C.[Sen-Ching],
Chuah, C.N.[Chen-Nee],
Joint Semi-supervised and Active Learning for Segmentation of
Gigapixel Pathology Images with Cost-Effective Labeling,
CDPath21(591-600)
IEEE DOI
2112
Training, Deep learning, Pathology, Image segmentation,
Image analysis, Manuals
BibRef
Marini, N.[Niccolň],
Atzori, M.[Manfredo],
Otálora, S.[Sebastian],
Marchand-Maillet, S.[Stephane],
Müller, H.[Henning],
H&E-adversarial network: a convolutional neural network to learn
stain-invariant features through Hematoxylin & Eosin regression,
CDPath21(601-610)
IEEE DOI
2112
Training, Image segmentation, Image color analysis, Histopathology,
Neural networks, Convolutional neural networks
BibRef
Deuschel, J.[Jessica],
Firmbach, D.[Daniel],
Geppert, C.I.[Carol I.],
Eckstein, M.[Markus],
Hartmann, A.[Arndt],
Bruns, V.[Volker],
Kuritcyn, P.[Petr],
Dexl, J.[Jakob],
Hartmann, D.[David],
Perrin, D.[Dominik],
Wittenberg, T.[Thomas],
Benz, M.[Michaela],
Multi-Prototype Few-shot Learning in Histopathology,
CDPath21(620-628)
IEEE DOI
2112
Training, Degradation, Histopathology, Neural networks,
Prototypes, Distributed databases
BibRef
Srinidhi, C.L.[Chetan L.],
Martel, A.L.[Anne L.],
Improving Self-supervised Learning with Hardness-aware Dynamic
Curriculum Learning: An Application to Digital Pathology,
CDPath21(562-571)
IEEE DOI
2112
Training, Visualization, Histopathology, Annotations,
Benchmark testing, Robustness, Complexity theory
BibRef
Tang, S.[Sheyang],
Hosseini, M.S.[Mahdi S.],
Chen, L.[Lina],
Varma, S.[Sonal],
Rowsell, C.[Corwyn],
Damaskinos, S.[Savvas],
Plataniotis, K.N.[Konstantinos N.],
Wang, Z.[Zhou],
Probeable DARTS with Application to Computational Pathology,
CDPath21(572-581)
IEEE DOI
2112
Measurement, Knowledge engineering, Pathology,
Computer network reliability, Robustness
BibRef
Gamper, J.[Jevgenij],
Rajpoot, N.[Nasir],
Multiple Instance Captioning: Learning Representations from
Histopathology Textbooks and Articles,
CVPR21(16544-16554)
IEEE DOI
2111
Histopathology, Computational modeling,
Estimation, Task analysis
BibRef
Zhang, J.W.[Jing-Wei],
Ma, K.[Ke],
van Arnam, J.[John],
Gupta, R.[Rajarsi],
Saltz, J.[Joel],
Vakalopoulou, M.[Maria],
Samaras, D.[Dimitris],
A Joint Spatial and Magnification Based Attention Framework for Large
Scale Histopathology Classification,
CVMI21(3771-3779)
IEEE DOI
2109
Training, Deep learning, Histopathology, Microscopy, Tools,
Probability distribution
BibRef
tepec, D.[Dejan],
Skocaj, D.[Danijel],
Unsupervised Detection of Cancerous Regions in Histology Imagery
using Image-to-Image Translation,
CVMI21(3780-3787)
IEEE DOI
2109
Visualization, Image analysis, Histopathology,
Biomedical measurement
BibRef
Wei, J.[Jerry],
Suriawinata, A.[Arief],
Ren, B.[Bing],
Liu, X.Y.[Xiao-Ying],
Lisovsky, M.[Mikhail],
Vaickus, L.[Louis],
Brown, C.[Charles],
Baker, M.[Michael],
Nasir-Moin, M.[Mustafa],
Tomita, N.[Naofumi],
Torresani, L.[Lorenzo],
Wei, J.[Jason],
Hassanpour, S.[Saeed],
Learn like a Pathologist: Curriculum Learning by Annotator Agreement
for Histopathology Image Classification,
WACV21(2472-2482)
IEEE DOI
2106
Training, Learning systems, Histopathology,
Task analysis, Image classification
BibRef
Belharbi, S.[Soufiane],
Ben Ayed, I.[Ismail],
McCaffrey, L.[Luke],
Granger, E.[Eric],
Deep Active Learning for Joint Classification Segmentation with Weak
Annotator,
WACV21(3337-3346)
IEEE DOI
2106
Training, Image segmentation, Visualization, Protocols, Annotations,
Histopathology, Training data
BibRef
Gong, X.[Xuan],
Chen, S.Y.[Shu-Yan],
Zhang, B.C.[Bao-Chang],
Doermann, D.[David],
Style Consistent Image Generation for Nuclei Instance Segmentation,
WACV21(3993-4002)
IEEE DOI
2106
Training, Image segmentation, Image analysis, Histopathology, Shape,
Image synthesis, Pipelines
BibRef
Zhao, S.[Shuai],
Li, X.[Xuanya],
Chen, Z.N.[Zhi-Neng],
Liu, C.[Chang],
Peng, C.G.[Chang-Gen],
Res2-unet: An Enhanced Network for Generalized Nuclear Segmentation in
Pathological Images,
MMMod21(II:87-98).
Springer DOI
2106
BibRef
Luo, J.Q.[Jia-Qi],
Zhao, Z.C.[Zhi-Cheng],
Su, F.[Fei],
Guo, L.[Limei],
Triplet-path Dilated Network for Detection and Segmentation of
General Pathological Images,
ICPR21(1452-1459)
IEEE DOI
2105
Image segmentation, Pathology, Visualization,
Object detection, Feature extraction, Robustness
BibRef
Yao, Z.Y.[Ze-Yi],
Li, K.Q.[Kai-Qi],
Luo, Y.W.[Yi-Wen],
Zhou, X.G.[Xiao-Guang],
Sun, M.[Muyi],
Zhang, G.H.[Guan-Hong],
Accurate Cell Segmentation in Digital Pathology Images via Attention
Enforced Networks,
ICPR21(1590-1595)
IEEE DOI
2105
Pathology, Image segmentation, Solid modeling, Design automation,
Image color analysis, Pipelines, Prediction algorithms,
digital pathology images
BibRef
Shin, B.[Beomjo],
Cho, J.[Junsu],
Yu, H.[Hwanjo],
Choi, S.J.[Seung-Jin],
Sparse Network Inversion for Key Instance Detection in Multiple
Instance Learning,
ICPR21(4083-4090)
IEEE DOI
2105
Training, Gradient methods, Histopathology, Neural networks,
Predictive models, Numerical models
BibRef
Ozen, Y.[Yigit],
Aksoy, S.[Selim],
Kösemehmetoglu, K.[Kemal],
Önder, S.[Sevgen],
Üner, A.[Aysegül],
Self-Supervised Learning with Graph Neural Networks for Region of
Interest Retrieval in Histopathology,
ICPR21(6329-6334)
IEEE DOI
2105
Training, Learning systems, Histopathology, Shape, Transfer learning,
Image retrieval, Breast, Digital pathology,
content-based image retrieval
BibRef
Sikaroudi, M.[Milad],
Ghojogh, B.[Benyamin],
Karray, F.[Fakhri],
Crowley, M.[Mark],
Tizhoosh, H.R.,
Batch-Incremental Triplet Sampling for Training Triplet Networks
Using Bayesian Updating Theorem,
ICPR21(7080-7086)
IEEE DOI
2105
Training, Histopathology, Training data, Stochastic processes,
Gaussian distribution, Bayes methods, Data mining
BibRef
Bussola, N.[Nicole],
Marcolini, A.[Alessia],
Maggio, V.[Valerio],
Jurman, G.[Giuseppe],
Furlanello, C.[Cesare],
AI Slipping on Tiles: Data Leakage in Digital Pathology,
AIDP20(167-182).
Springer DOI
2103
Reproducible results.
BibRef
Sikaroudi, M.[Milad],
Ghojogh, B.[Benyamin],
Safarpoor, A.[Amir],
Karray, F.[Fakhri],
Crowley, M.[Mark],
Tizhoosh, H.R.[Hamid R.],
Offline Versus Online Triplet Mining Based on Extreme Distances of
Histopathology Patches,
ISVC20(I:333-345).
Springer DOI
2103
BibRef
Maleki, D.[Danial],
Afshari, M.[Mehdi],
Babaie, M.[Morteza],
Tizhoosh, H.R.,
Ink Marker Segmentation in Histopathology Images Using Deep Learning,
ISVC20(I:359-368).
Springer DOI
2103
BibRef
Cheng, H.T.[Hsien-Tzu],
Yeh, C.F.[Chun-Fu],
Kuo, P.C.[Po-Chen],
Wei, A.[Andy],
Liu, K.C.[Keng-Chi],
Ko, M.C.[Mong-Chi],
Chao, K.H.[Kuan-Hua],
Peng, Y.C.[Yu-Ching],
Liu, T.L.[Tyng-Luh],
Self-similarity Student for Partial Label Histopathology Image
Segmentation,
ECCV20(XXV:117-132).
Springer DOI
2011
BibRef
Xiang, Y.,
Chen, J.,
Liu, Q.,
Liang, Y.,
Disentangled Representation Learning Based Multidomain Stain
Normalization For Histological Images,
ICIP20(360-364)
IEEE DOI
2011
Image color analysis, Image reconstruction,
Generative adversarial networks, Training, Decoding, Generators,
Deep Learning
BibRef
Hosseini, M.S.[Mahdi S.],
Chan, L.[Lyndon],
Huang, W.M.[Wei-Min],
Wang, Y.C.[Yi-Chen],
Hasan, D.[Danial],
Rowsell, C.[Corwyn],
Damaskinos, S.[Savvas],
Plataniotis, K.N.[Konstantinos N.],
On Transferability of Histological Tissue Labels in Computational
Pathology,
ECCV20(XXIX: 453-469).
Springer DOI
2010
BibRef
Cheeseman, A.K.[Alison K.],
Tizhoosh, H.R.[Hamid R.],
Vrscay, E.R.[Edward R.],
Studying the Effect of Digital Stain Separation of Histopathology
Images on Image Search Performance,
ICIAR20(II:262-273).
Springer DOI
2007
BibRef
Alinsaif, S.,
Lang, J.,
Histological Image Classification using Deep Features and Transfer
Learning,
CRV20(101-108)
IEEE DOI
2006
Deep learning, Fine-tuning, CNN-Based Features, histopathological,
SVM, classification
BibRef
Hosseini, M.S.[Mahdi S.],
Chan, L.[Lyndon],
Tse, G.[Gabriel],
Tang, M.[Michael],
Deng, J.[Jun],
Norouzi, S.[Sajad],
Rowsell, C.[Corwyn],
Plataniotis, K.N.[Konstantinos N.],
Damaskinos, S.[Savvas],
Atlas of Digital Pathology: A Generalized Hierarchical Histological
Tissue Type-Annotated Database for Deep Learning,
CVPR19(11739-11748).
IEEE DOI
2002
BibRef
Hou, L.[Le],
Agarwal, A.[Ayush],
Samaras, D.[Dimitris],
Kurc, T.M.[Tahsin M.],
Gupta, R.R.[Rajarsi R.],
Saltz, J.H.[Joel H.],
Robust Histopathology Image Analysis: To Label or to Synthesize?,
CVPR19(8525-8534).
IEEE DOI
2002
BibRef
Xu, G.,
Song, Z.,
Sun, Z.,
Ku, C.,
Yang, Z.,
Liu, C.,
Wang, S.,
Ma, J.,
Xu, W.,
CAMEL: A Weakly Supervised Learning Framework for Histopathology
Image Segmentation,
ICCV19(10681-10690)
IEEE DOI
2004
cancer, image classification, image segmentation,
learning (artificial intelligence), medical image processing,
Feature extraction
BibRef
Bidart, R.[Rene],
Wong, A.[Alexander],
TriResNet: A Deep Triple-Stream Residual Network for Histopathology
Grading,
ICIAR19(II:369-382).
Springer DOI
1909
BibRef
Cheeseman, A.K.[Alison K.],
Tizhoosh, H.[Hamid],
Vrscay, E.R.[Edward R.],
A Compact Representation of Histopathology Images Using Digital Stain
Separation and Frequency-Based Encoded Local Projections,
ICIAR19(II:147-158).
Springer DOI
1909
BibRef
Kieffer, B.,
Babaie, M.,
Kalra, S.,
Tizhoosh, H.R.,
Convolutional neural networks for histopathology image
classification: Training vs. Using pre-trained networks,
IPTA17(1-6)
IEEE DOI
1804
feature extraction, image classification, image representation,
learning (artificial intelligence), medical image processing,
medical imaging
BibRef
Valkonen, M.,
Kartasalo, K.,
Liimatainen, K.,
Nykter, M.,
Latonen, L.,
Ruusuvuori, P.,
Dual Structured Convolutional Neural Network with Feature
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BioIm17(27-35)
IEEE DOI
1802
Biological system modeling, Feature extraction, Histograms,
Image analysis, Pathology, Training
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Li, W.,
Qian, X.,
Ji, J.,
Noise-tolerant deep learning for histopathological image segmentation,
ICIP17(3075-3079)
IEEE DOI
1803
Diseases, Image color analysis, Image segmentation,
Machine learning, Muscles, Noise measurement, Training,
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Stain separation in digital bright field histopathology,
IPTA16(1-6)
IEEE DOI
1703
biological tissues
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Agarwal, N.[Nitin],
Xu, X.M.[Xiang-Min],
Gopi, M.,
Automatic Detection of Histological Artifacts in Mouse Brain Slice
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MCV16(105-115).
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1711
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Corredor, G.[German],
Romero, E.[Eduardo],
Learning histopathological regions of interest by fusing bottom-up
and top-down information,
ICIP15(3200-3204)
IEEE DOI
1512
Histopathology
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Li, X.Y.[Xing-Yu],
Plataniotis, K.N.[Konstantinos N.],
Diagnostic color estimation of tissue components in pathology images
via von Mises mixture model,
ICIP15(2060-2064)
IEEE DOI
1512
Pathology image
BibRef
Hatipoglu, N.,
Bilgin, G.,
Classification of histopathological images using convolutional neural
network,
IPTA14(1-6)
IEEE DOI
1503
image classification
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McCann, M.T.[Michael T.],
Majumdar, J.[Joshita],
Peng, C.[Cheng],
Castro, C.A.[Carlos A.],
Kovacevic, J.[Jelena],
Algorithm and benchmark dataset for stain separation in histology
images,
ICIP14(3953-3957)
IEEE DOI
1502
Accuracy
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Sommer, C.[Christoph],
Fiaschi, L.[Luca],
Hamprecht, F.A.[Fred A.],
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Learning-based mitotic cell detection in histopathological images,
ICPR12(2306-2309).
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1302
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Díaz, G.[Gloria],
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Histopathological Image Classification Using Stain Component Features
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CIARP10(55-62).
Springer DOI
1011
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Cooper, L.[Lee],
Saltz, J.[Joel],
Machiraju, R.[Raghu],
Huang, K.[Kun],
Two-point correlation as a feature for histology images:
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MMBIA10(79-86).
IEEE DOI
1006
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Graf, F.[Felix],
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Counting Lymphocytes in Histopathology Images Using Connected
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ICPR-Contests10(263-269).
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1008
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Cheng, J.[Jierong],
Veronika, M.[Merlin],
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Identifying Cells in Histopathological Images,
ICPR-Contests10(244-252).
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1008
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Kuse, M.[Manohar],
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Gupta, S.[Sudhir],
A Classification Scheme for Lymphocyte Segmentation in H&E Stained
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ICPR-Contests10(235-243).
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1008
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Gurcan, M.N.[Metin N.],
Madabhushi, A.[Anant],
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Pattern Recognition in Histopathological Images: An ICPR 2010 Contest,
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1008
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Thomas, K.A.[Kristine A.],
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Unsupervised Segmentation for Inflammation Detection in Histopathology
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IEEE DOI
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Statistical Categorization of Human Histological Images,
ICIP05(III: 628-631).
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0512
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Roula, M.A.,
Bouridane, A.,
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An evolutionary snake algorithm for the segmentation of nuclei in
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ICIP04(I: 127-130).
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0505
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Nedzved, A.,
Ablameyko, S.V.,
Pitas, I.,
Morphological Segmentation of Histology Cell Images,
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0009
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Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Whole Slide Analysis, Histopahtology, Cells .