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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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2112
Image registration, Histopathological image, Multi-view,
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2201
Glands, Image segmentation, Semantics, Feature extraction,
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2202
Feature extraction, Predictive models, Correlation, Hazards,
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2203
Image segmentation, Uncertainty, Histopathology, Predictive models,
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2204
Noise measurement, Training, Histopathology, Noise robustness,
Image classification, Data models, Predictive models,
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Wang, Z.C.[Zi-Chen],
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IEEE DOI
2205
Noise measurement, Annotations, Training, Biomedical imaging,
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2206
2-D RNN, Conditional random field, Detail preservation,
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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,
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Abousamra, S.[Shahira],
Belinsky, D.[David],
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Saltz, J.[Joel],
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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,
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Wang, H.T.[Hao-Tian],
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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
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Dardikman-Yoffe, G.[Gilli],
Eldar, Y.C.[Yonina C.],
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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
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Zhao, K.[Kun],
Jennings, A.[Anthony],
Hobson, P.[Peter],
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Baker, B.[Brett],
Staweno, J.[Justin],
Lovell, B.C.[Brian C.],
Efficient DNN-Based Classification of Whole Slide Gram Stain Images
for Microbiology,
DICTA21(01-08)
IEEE DOI
2201
Training, Deep learning, Pathology, Microorganisms, Protocols, Oils,
Microscopy, Bacteria Classification, DNN, Computer Aided Diagnosis,
Digital Pathology
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Shen, Y.Q.[Yi-Qing],
Ke, J.[Jing],
Su-Sampling Based Active Learning for Large-Scale Histopathology
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ICIP21(116-120)
IEEE DOI
2201
Deep learning, Image segmentation, Uncertainty,
Monte Carlo methods, Annotations, Histopathology, Neural networks,
convolutional neural network
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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
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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.[Niccolò],
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
Weitz, P.[Philippe],
Wang, Y.[Yinxi],
Hartman, J.[Johan],
Rantalainen, M.[Mattias],
An investigation of attention mechanisms in histopathology
whole-slide-image analysis for regression objectives,
CDPath21(611-619)
IEEE DOI
2112
Analytical models, Histopathology,
Computational modeling, Focusing, Predictive models
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, Pattern recognition, Task analysis
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CVMI21(3771-3779)
IEEE DOI
2109
Training, Deep learning, Histopathology, Microscopy, Tools,
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Unsupervised Detection of Cancerous Regions in Histology Imagery
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CVMI21(3780-3787)
IEEE DOI
2109
Visualization, Image analysis, Histopathology,
Biomedical measurement, Pattern recognition
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Wei, J.[Jerry],
Suriawinata, A.[Arief],
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WACV21(2472-2482)
IEEE DOI
2106
Training, Learning systems, Histopathology,
Task analysis, Image classification
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Belharbi, S.[Soufiane],
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WACV21(3337-3346)
IEEE DOI
2106
Training, Image segmentation, Visualization, Protocols, Annotations,
Histopathology, Training data
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Gong, X.[Xuan],
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Style Consistent Image Generation for Nuclei Instance Segmentation,
WACV21(3993-4002)
IEEE DOI
2106
Training, Image segmentation, Image analysis, Histopathology, Shape,
Image synthesis, Pipelines
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Zhao, S.[Shuai],
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2106
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ICPR21(1452-1459)
IEEE DOI
2105
Image segmentation, Pathology, Visualization,
Object detection, Feature extraction, Robustness
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Yao, Z.Y.[Ze-Yi],
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Accurate Cell Segmentation in Digital Pathology Images via Attention
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ICPR21(1590-1595)
IEEE DOI
2105
Pathology, Image segmentation, Solid modeling, Design automation,
Image color analysis, Pipelines, Prediction algorithms,
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Shin, B.[Beomjo],
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ICPR21(4083-4090)
IEEE DOI
2105
Training, Gradient methods, Histopathology, Neural networks,
Predictive models, Pattern recognition, Numerical models
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Ozen, Y.[Yigit],
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Self-Supervised Learning with Graph Neural Networks for Region of
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ICPR21(6329-6334)
IEEE DOI
2105
Training, Learning systems, Histopathology, Shape, Transfer learning,
Image retrieval, Breast, Digital pathology,
content-based image retrieval
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Sikaroudi, M.[Milad],
Ghojogh, B.[Benyamin],
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Batch-Incremental Triplet Sampling for Training Triplet Networks
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ICPR21(7080-7086)
IEEE DOI
2105
Training, Histopathology, Training data, Stochastic processes,
Gaussian distribution, Bayes methods, Data mining
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AI Slipping on Tiles: Data Leakage in Digital Pathology,
AIDP20(167-182).
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2103
Reproducible results.
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2103
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2103
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Cheng, H.T.[Hsien-Tzu],
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Disentangled Representation Learning Based Multidomain Stain
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ICIP20(360-364)
IEEE DOI
2011
Image color analysis, Image reconstruction,
Generative adversarial networks, Training, Decoding, Generators,
Deep Learning
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Chan, L.[Lyndon],
Huang, W.M.[Wei-Min],
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2007
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Histological Image Classification using Deep Features and Transfer
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CRV20(101-108)
IEEE DOI
2006
Deep learning, Fine-tuning, CNN-Based Features, histopathological,
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Chan, L.[Lyndon],
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IEEE DOI
2002
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1905
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Convolutional neural networks for histopathology image
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IPTA17(1-6)
IEEE DOI
1804
feature extraction, image classification, image representation,
learning (artificial intelligence), medical image processing,
medical imaging
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Kartasalo, K.,
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Dual Structured Convolutional Neural Network with Feature
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BioIm17(27-35)
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1802
Biological system modeling, Feature extraction, Histograms,
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Li, W.,
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Noise-tolerant deep learning for histopathological image segmentation,
ICIP17(3075-3079)
IEEE DOI
1803
Diseases, Image color analysis, Image segmentation,
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Stain separation in digital bright field histopathology,
IPTA16(1-6)
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biological tissues
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Automatic Detection of Histological Artifacts in Mouse Brain Slice
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ICIP15(3200-3204)
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Histopathology
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ICIP15(2060-2064)
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1512
Pathology image
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Classification of histopathological images using convolutional neural
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IPTA14(1-6)
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image classification
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ICIP14(3953-3957)
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Accuracy
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Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Fluorescence Analysis, Microscopic Analysis, Cells .