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Image segmentation, Biomedical imaging, Training, Annotations,
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2110
Image segmentation, Training, Annotations, Shape, Biomedical imaging,
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Image segmentation, Computer architecture, Semantics,
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Uncertainty, Image segmentation, Estimation, Training,
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Image segmentation, Task analysis, Training, Biomedical imaging,
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2K-Fold-Net, EF-Net, U-Net, AFE, Image segmentation
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2205
Medical image segmentation, Dynamic scale-aware context,
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Code, Segmentation.
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2209
Feature extraction, Image reconstruction, Semantics,
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2212
Image segmentation, Pathology, Training, Manuals, Annotations,
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MsVRL: Self-Supervised Multiscale Visual Representation Learning via
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2301
Image segmentation, Task analysis, Visualization,
Self-supervised learning, Medical diagnostic imaging, abdomen
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Domain and Content Adaptive Convolution Based Multi-Source Domain
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IEEE DOI
2301
Image segmentation, Adaptation models, Head, Biomedical imaging,
Convolution, Training, Data models, Domain generalization,
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Elsevier DOI
2301
Deep learning, Segmentation, Medical imaging, Loss function
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2301
Transformer, Medical image segmentation,
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IEEE DOI
2303
Annotations, Image segmentation, Training, Biomedical imaging,
Task analysis, Shape, 3D medical image segmentation,
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CVPR23(3302-3311)
IEEE DOI
2309
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Sun, M.[Muyi],
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Graph Flow: Cross-Layer Graph Flow Distillation for Dual Efficient
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IEEE DOI
2304
Image segmentation, Knowledge engineering,
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2304
biomedical engineering, image segmentation,
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Elsevier DOI
2305
Medical image segmentation, Geometric structure learning,
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Data Discernment for Affordable Training in Medical Image
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MedImg(42), No. 5, May 2023, pp. 1431-1445.
IEEE DOI
2305
Training, Image segmentation, Biomedical imaging, Task analysis,
Training data, Programming, Annotations, Data discernment,
medical image segmentation
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Huang, X.H.[Xiao-Hong],
Deng, Z.F.[Zhi-Fang],
Li, D.D.[Dan-Dan],
Yuan, X.G.[Xue-Guang],
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MISSFormer: An Effective Transformer for 2D Medical Image
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MedImg(42), No. 5, May 2023, pp. 1484-1494.
IEEE DOI
2305
Transformers, Image segmentation, Task analysis, Bridges,
Medical diagnostic imaging, Feature extraction, Merging,
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DOI Link
2305
dropout residual graph convolution block, edge attention gate,
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Kamnitsas, K.[Konstantinos],
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MedImg(42), No. 6, June 2023, pp. 1885-1896.
IEEE DOI
2306
Image segmentation, Tumors, Task analysis, Liver, Kidney, Context modeling,
Training, Underfitting, multi-task learning, image segmentation
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Fang, C.W.[Chao-Wei],
Wang, Q.[Qian],
Cheng, L.[Lechao],
Gao, Z.F.[Zhi-Fan],
Pan, C.W.[Cheng-Wei],
Cao, Z.[Zhen],
Zheng, Z.H.[Zhao-Hui],
Zhang, D.W.[Ding-Wen],
Reliable Mutual Distillation for Medical Image Segmentation Under
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MedImg(42), No. 6, June 2023, pp. 1720-1734.
IEEE DOI
2306
Image segmentation, Reliability, Annotations, Noise measurement,
Data models, Training, Cleaning, Imperfect annotation,
medical image segmentation
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Xian, J.L.[Jun-Lin],
Li, X.[Xiang],
Tu, D.D.[Dan-Dan],
Zhu, S.[Senhua],
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Liu, X.W.[Xiao-Wu],
Li, X.[Xin],
Yang, X.[Xin],
Unsupervised Cross-Modality Adaptation via Dual Structural-Oriented
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MedImg(42), No. 6, June 2023, pp. 1774-1785.
IEEE DOI
2306
Image segmentation, Biomedical imaging, Feature extraction,
Training, Magnetic resonance imaging, Computed tomography,
structural-oriented guidance
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Li, H.[Hengbo],
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Cross-Mix Monitoring for Medical Image Segmentation With Limited
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MultMed(25), 2023, pp. 1700-1712.
IEEE DOI
2306
Image segmentation, Biomedical imaging, Training, Data models,
Perturbation methods, Task analysis, Monitoring, transductive monitor
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Lyu, Y.D.[Ying-Da],
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IVC(135), 2023, pp. 104694.
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2306
Complementary feature, Contrastive feature, Mutual attention,
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Wang, X.[Xuan],
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Semi-Supervised Medical Image Segmentation Using Adversarial
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MedImg(42), No. 5, May 2023, pp. 1265-1277.
IEEE DOI
2305
Image segmentation, Training, Data models, Perturbation methods,
Medical diagnostic imaging, Convolution, adversarial learning
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Deep Generative Adversarial Reinforcement Learning for
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MedImg(43), No. 9, September 2024, pp. 3072-3084.
IEEE DOI
2409
Image segmentation, Task analysis, Biomedical imaging,
Generative adversarial networks, Optimization, Training,
generative adversarial networks (GANs)
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Cheng, K.T.[Kwang-Ting],
FedMix: Mixed Supervised Federated Learning for Medical Image
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MedImg(42), No. 7, July 2023, pp. 1955-1968.
IEEE DOI
2307
Image segmentation, Data models, Biomedical imaging, Training,
Federated learning, Lesions, Adaptation models, Federated learning,
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Jiang, M.[Meirui],
Yang, H.Z.[Hong-Zheng],
Cheng, C.[Chen],
Dou, Q.[Qi],
IOP-FL: Inside-Outside Personalization for Federated Medical Image
Segmentation,
MedImg(42), No. 7, July 2023, pp. 2106-2117.
IEEE DOI
2307
Adaptation models, Data models, Training, Routing,
Image segmentation, Biomedical imaging, Task analysis,
data heterogeneity
BibRef
Gao, Z.[Zheyao],
Wu, F.[Fuping],
Gao, W.G.[Wei-Guo],
Zhuang, X.[Xiahai],
A New Framework of Swarm Learning Consolidating Knowledge From
Multi-Center Non-IID Data for Medical Image Segmentation,
MedImg(42), No. 7, July 2023, pp. 2118-2129.
IEEE DOI
2307
Image segmentation, Training, Data models, Task analysis,
Biomedical imaging, Distributed databases, Distance learning,
swarm learning
BibRef
Lin, X.[Xian],
Yu, L.[Li],
Cheng, K.T.[Kwang-Ting],
Yan, Z.Q.[Zeng-Qiang],
The Lighter the Better: Rethinking Transformers in Medical Image
Segmentation Through Adaptive Pruning,
MedImg(42), No. 8, August 2023, pp. 2325-2337.
IEEE DOI
2308
Transformers, Biomedical imaging, Image segmentation, Training,
Task analysis, Computational complexity, Costs, Adaptive pruning, transformer
BibRef
Huang, S.Q.[Shi-Qi],
Xu, T.F.[Ting-Fa],
Shen, N.[Ning],
Mu, F.[Feng],
Li, J.A.[Jian-An],
Rethinking Few-Shot Medical Segmentation: A Vector Quantization View,
CVPR23(3072-3081)
IEEE DOI
2309
BibRef
Chen, Y.Z.[Yi-Zheng],
Yu, L.Q.[Le-Quan],
Wang, J.Y.[Jen-Yeu],
Panjwani, N.[Neil],
Obeid, J.P.[Jean-Pierre],
Liu, W.[Wu],
Liu, L.[Lianli],
Kovalchuk, N.[Nataliya],
Gensheimer, M.F.[Michael Francis],
Vitzthum, L.K.[Lucas Kas],
Beadle, B.M.[Beth M.],
Chang, D.T.[Daniel T.],
Le, Q.T.[Quynh-Thu],
Han, B.[Bin],
Xing, L.[Lei],
Adaptive Region-Specific Loss for Improved Medical Image Segmentation,
PAMI(45), No. 11, November 2023, pp. 13408-13421.
IEEE DOI
2310
BibRef
He, A.[Along],
Wang, K.[Kai],
Li, T.[Tao],
Du, C.K.[Cheng-Kun],
Xia, S.[Shuang],
Fu, H.Z.[Hua-Zhu],
H2Former: An Efficient Hierarchical Hybrid Transformer for Medical
Image Segmentation,
MedImg(42), No. 9, September 2023, pp. 2763-2775.
IEEE DOI
2310
BibRef
Wang, N.[Nan],
Lin, S.H.[Shao-Hui],
Li, X.X.[Xiao-Xiao],
Li, K.[Ke],
Shen, Y.[Yunhang],
Gao, Y.[Yue],
Ma, L.Z.[Li-Zhuang],
MISSU: 3D Medical Image Segmentation via Self-Distilling TransUNet,
MedImg(42), No. 9, September 2023, pp. 2740-2750.
IEEE DOI
2310
BibRef
Du, H.[Hao],
Dong, Q.H.[Qi-Hua],
Xu, Y.[Yan],
Liao, J.[Jing],
Weakly-Supervised 3D Medical Image Segmentation Using Geometric Prior
and Contrastive Similarity,
MedImg(42), No. 10, October 2023, pp. 2936-2947.
IEEE DOI
2310
BibRef
Zhang, J.Y.[Jing-Yang],
Gu, R.[Ran],
Xue, P.[Peng],
Liu, M.X.[Mian-Xin],
Zheng, H.[Hao],
Zheng, Y.F.[Ye-Feng],
Ma, L.[Lei],
Wang, G.[Guotai],
Gu, L.[Lixu],
S3R: Shape and Semantics-Based Selective Regularization for
Explainable Continual Segmentation Across Multiple Sites,
MedImg(42), No. 9, September 2023, pp. 2539-2551.
IEEE DOI
2310
BibRef
Xu, M.C.[Mou-Cheng],
Zhou, Y.K.[Yu-Kun],
Jin, C.[Chen],
de Groot, M.[Marius],
Alexander, D.C.[Daniel C.],
Oxtoby, N.P.[Neil P.],
Jacob, J.[Joseph],
MisMatch: Calibrated Segmentation via Consistency on Differential
Morphological Feature Perturbations With Limited Labels,
MedImg(42), No. 10, October 2023, pp. 2988-2999.
IEEE DOI
2310
BibRef
Wang, S.S.[Sheng-Sheng],
Fu, Z.[Zihao],
Wang, B.L.[Bi-Lin],
Hu, Y.L.[Yu-Long],
Fusing feature and output space for unsupervised domain adaptation on
medical image segmentation,
IJIST(33), No. 5, 2023, pp. 1672-1681.
DOI Link
2310
adversarial domain adaptation, domain adaptation,
image segmentation, medical image
BibRef
Pang, S.C.[Shu-Chao],
Du, A.[Anan],
Orgun, M.A.[Mehmet A.],
Wang, Y.[Yan],
Sheng, Q.Z.[Quan Z.],
Wang, S.J.[Shou-Jin],
Huang, X.S.[Xiao-Shui],
Yu, Z.M.[Zhen-Mei],
Beyond CNNs:
Exploiting Further Inherent Symmetries in Medical Image Segmentation,
Cyber(53), No. 11, November 2023, pp. 6776-6787.
IEEE DOI
2310
BibRef
Liu, S.[Shidi],
Liu, C.P.[Chun-Ping],
Ji, Y.[Yi],
Li, Y.[Ying],
Regional Consistency for Semi-Supervised Segmentation of 3D Medical
Images,
SPLetters(30), 2023, pp. 1307-1311.
IEEE DOI
2310
BibRef
Wu, H.M.[Hui-Min],
Li, X.M.[Xiao-Meng],
Lin, Y.Q.[Yi-Qun],
Cheng, K.T.[Kwang-Ting],
Compete to Win: Enhancing Pseudo Labels for Barely-Supervised Medical
Image Segmentation,
MedImg(42), No. 11, November 2023, pp. 3244-3255.
IEEE DOI Code:
WWW Link.
2311
BibRef
Li, Z.[Zeju],
Kamnitsas, K.[Konstantinos],
Dou, Q.[Qi],
Qin, C.[Chen],
Glocker, B.[Ben],
Joint Optimization of Class-Specific Training- and Test-Time Data
Augmentation in Segmentation,
MedImg(42), No. 11, November 2023, pp. 3323-3335.
IEEE DOI Code:
WWW Link.
2311
BibRef
Ji, Q.L.[Qiu-Lang],
Wang, J.H.[Ji-Hong],
Ding, C.[Caifu],
Wang, Y.H.[Yu-Hang],
Zhou, W.[Wen],
Liu, Z.J.[Zi-Jie],
Yang, C.[Chen],
DMAGNet: Dual-path multi-scale attention guided network for medical
image segmentation,
IET-IPR(17), No. 13, 2023, pp. 3631-3644.
DOI Link
2311
codecs, convolutional neural nets, image processing, image segmentation
BibRef
Tang, C.[Cheng],
Zeng, X.[Xinyi],
Zhou, L.P.[Lu-Ping],
Zhou, Q.Z.[Qi-Zheng],
Wang, P.[Peng],
Wu, X.[Xi],
Ren, H.P.[Hong-Ping],
Zhou, J.[Jiliu],
Wang, Y.[Yan],
Semi-supervised medical image segmentation via hard positives
oriented contrastive learning,
PR(146), 2024, pp. 110020.
Elsevier DOI Code:
WWW Link.
2311
Hard positives, Contrastive learning, Semi-supervised learning,
Medical image segmentation
BibRef
Chen, J.K.[Jing-Kun],
Chen, C.R.[Chang-Rui],
Huang, W.J.[Wen-Jian],
Zhang, J.G.[Jian-Guo],
Debattista, K.[Kurt],
Han, J.G.[Jun-Gong],
Dynamic contrastive learning guided by class confidence and confusion
degree for medical image segmentation,
PR(145), 2024, pp. 109881.
Elsevier DOI
2311
Class confusion degree, Dynamic contrastive learning, Medical image segmentation
BibRef
Qiu, Z.X.[Zhong-Xi],
Hu, Y.[Yan],
Chen, X.S.[Xiao-Shan],
Zeng, D.[Dan],
Hu, Q.Y.[Qing-Yong],
Liu, J.[Jiang],
Rethinking Dual-Stream Super-Resolution Semantic Learning in Medical
Image Segmentation,
PAMI(46), No. 1, January 2024, pp. 451-464.
IEEE DOI
2312
BibRef
Zhang, J.J.[Jiao-Jiao],
Zhang, S.[Shuo],
Shen, X.Q.[Xiao-Qian],
Lukasiewicz, T.[Thomas],
Xu, Z.H.[Zheng-Hua],
Multi-ConDoS: Multimodal Contrastive Domain Sharing Generative
Adversarial Networks for Self-Supervised Medical Image Segmentation,
MedImg(43), No. 1, January 2024, pp. 76-95.
IEEE DOI
2401
BibRef
Xu, Z.H.[Zheng-Hua],
Liu, Y.X.[Yun-Xin],
Xu, G.[Gang],
Lukasiewicz, T.[Thomas],
Self-Supervised Medical Image Segmentation Using Deep Reinforced
Adaptive Masking,
MedImg(44), No. 1, January 2025, pp. 180-193.
IEEE DOI
2501
Biomedical imaging, Image reconstruction, Image segmentation,
Task analysis, Adaptation models, Self-supervised learning,
deep reinforcement learning
BibRef
Lei, W.H.[Wen-Hui],
Su, Q.[Qi],
Jiang, T.Y.[Tian-Yu],
Gu, R.[Ran],
Wang, N.[Na],
Liu, X.L.[Xing-Long],
Wang, G.[Guotai],
Zhang, X.F.[Xiao-Fan],
Zhang, S.T.[Shao-Ting],
One-Shot Weakly-Supervised Segmentation in 3D Medical Images,
MedImg(43), No. 1, January 2024, pp. 175-189.
IEEE DOI Code:
WWW Link.
2401
BibRef
Wang, J.C.[Jia-Cheng],
Jin, Y.M.[Yue-Ming],
Stoyanov, D.[Danail],
Wang, L.S.[Lian-Sheng],
FedDP: Dual Personalization in Federated Medical Image Segmentation,
MedImg(43), No. 1, January 2024, pp. 297-308.
IEEE DOI Code:
WWW Link.
2401
BibRef
Earlier: A1, A2, A4, Only:
Personalizing Federated Medical Image Segmentation via Local
Calibration,
ECCV22(XXI:456-472).
Springer DOI
2211
BibRef
Tong, S.S.[Shan-Shan],
Zuo, Z.T.[Zhen-Tao],
Liu, Z.[Zuxiang],
Sun, D.[Dengdi],
Zhou, T.G.[Tian-Gang],
Hybrid attention mechanism of feature fusion for medical image
segmentation,
IET-IPR(18), No. 1, 2024, pp. 77-87.
DOI Link
2401
biomedical imaging, image segmentation, medical image processing
BibRef
Lu, C.Z.[Cheng-Zhun],
Xia, Z.R.[Zhang-Run],
Przystupa, K.[Krzysztof],
Kochan, O.[Orest],
Su, J.[Jun],
DCELANM-Net: Medical image segmentation based on dual channel
efficient layer aggregation network with learner,
IJIST(34), No. 1, 2024, pp. e22960.
DOI Link
2401
CNN, medical image segmentation, self-supervised learning, transformer
BibRef
Zhao, Y.Y.[Yi-Yang],
Li, J.J.[Jin-Jiang],
Liu, Y.P.[Ye-Peng],
Dynamic weight HiLo attention network for medical image multiple
organ segmentation,
IJIST(34), No. 1, 2024, pp. e22966.
DOI Link
2401
attention mechanism, convolutional neural networks,
medical image segmentation, multiscale feature extraction
BibRef
Ming, Q.[Qi],
Xiao, X.W.[Xiao-Wu],
Towards Accurate Medical Image Segmentation with Gradient-Optimized
Dice Loss,
SPLetters(31), 2024, pp. 191-195.
IEEE DOI
2401
BibRef
Pang, Y.[Yan],
Liang, J.[JiaMing],
Huang, T.[Teng],
Chen, H.[Hao],
Li, Y.H.[Yun-Hao],
Li, D.[Dan],
Huang, L.[Lin],
Wang, Q.[Qiong],
Slim UNETR: Scale Hybrid Transformers to Efficient 3D Medical Image
Segmentation Under Limited Computational Resources,
MedImg(43), No. 3, March 2024, pp. 994-1005.
IEEE DOI Code:
WWW Link.
2403
Biomedical imaging, Transformers, Image segmentation, Task analysis,
Computational modeling, Solid modeling, resource-limited application
BibRef
Han, X.J.[Xian-Jun],
Li, T.T.[Tian-Tian],
Bai, C.[Can],
Yang, H.Y.[Hong-Yu],
Integrating prior knowledge into a bibranch pyramid network for
medical image segmentation,
IVC(143), 2024, pp. 104945.
Elsevier DOI
2403
Image pyramid, Medical image segmentation, Prior knowledge,
Medical image processing
BibRef
Li, H.[Hao],
Zhai, D.H.[Di-Hua],
Xia, Y.Q.[Yuan-Qing],
ERDUnet: An Efficient Residual Double-Coding Unet for Medical Image
Segmentation,
CirSysVideo(34), No. 4, April 2024, pp. 2083-2096.
IEEE DOI Code:
WWW Link.
2404
Image segmentation, Feature extraction,
Medical diagnostic imaging, Lesions, Transformers, Encoding,
reduce parameter scale
BibRef
Huang, Z.M.[Zhong-Miao],
Cheng, S.[Shuli],
Wang, L.J.[Lie-Jun],
Medical image segmentation based on dynamic positioning and
region-aware attention,
PR(151), 2024, pp. 110375.
Elsevier DOI
2404
Medical image segmentation, Transformer,
Dynamic Positioning Attention, Bi-Level Routing Attention
BibRef
Guo, X.[Xiayu],
Lin, X.[Xian],
Yang, X.[Xin],
Yu, L.[Li],
Cheng, K.T.[Kwang-Ting],
Yan, Z.Q.[Zeng-Qiang],
UCTNet: Uncertainty-guided CNN-Transformer hybrid networks for
medical image segmentation,
PR(152), 2024, pp. 110491.
Elsevier DOI Code:
WWW Link.
2405
CNN-Transformer hybrid, Uncertainty, Functional overlap,
Masked self-attention, Medical image segmentation
BibRef
He, A.[Along],
Li, T.[Tao],
Yan, J.C.[Jun-Cheng],
Wang, K.[Kai],
Fu, H.Z.[Hua-Zhu],
Bilateral Supervision Network for Semi-Supervised Medical Image
Segmentation,
MedImg(43), No. 5, May 2024, pp. 1715-1726.
IEEE DOI
2405
Image segmentation, Training, Data models,
Adversarial machine learning, Task analysis, Uncertainty,
medical image segmentation
BibRef
Ma, Y.X.[Yu-Xi],
Wang, J.C.[Jia-Cheng],
Yang, J.[Jing],
Wang, L.S.[Lian-Sheng],
Model-Heterogeneous Semi-Supervised Federated Learning for Medical
Image Segmentation,
MedImg(43), No. 5, May 2024, pp. 1804-1815.
IEEE DOI
2405
Training, Data models, Federated learning, Semisupervised learning,
Annotations, Servers, Predictive models, Federated learning,
semi-supervised learning
BibRef
Cheng, Z.M.[Zi-Ming],
Wang, S.D.[Shi-Dong],
Xin, T.[Tong],
Zhou, T.[Tao],
Zhang, H.F.[Hao-Feng],
Shao, L.[Ling],
Few-Shot Medical Image Segmentation via Generating Multiple
Representative Descriptors,
MedImg(43), No. 6, June 2024, pp. 2202-2214.
IEEE DOI
2406
Image segmentation, Biomedical imaging, Prototypes, Task analysis,
Training, Semantic segmentation, Feature extraction,
imbalance alleviation
BibRef
Zhu, Y.Z.[Ya-Zhou],
Cheng, Z.M.[Zi-Ming],
Wang, S.D.[Shi-Dong],
Zhang, H.F.[Hao-Feng],
Learning De-biased prototypes for Few-shot Medical Image Segmentation,
PRL(183), 2024, pp. 71-77.
Elsevier DOI Code:
WWW Link.
2406
Few-shot learning, Medical image segmentation,
De-biased prototypes, Learnable threshold
BibRef
Liu, X.Q.[Xiao-Qing],
Ono, K.[Kenji],
Bise, R.[Ryoma],
A data augmentation approach that ensures the reliability of
foregrounds in medical image segmentation,
IVC(147), 2024, pp. 105056.
Elsevier DOI
2406
Medical image analysis, Medical image segmentation, Data augmentation
BibRef
Wang, Z.B.[Zhi-Bing],
Wang, W.M.[Wen-Min],
Li, N.N.[Nan-Nan],
Zhang, S.Y.[Shen-Yong],
Chen, Q.[Qi],
Jiang, Z.[Zhe],
Multimodal parallel attention network for medical image segmentation,
IVC(147), 2024, pp. 105069.
Elsevier DOI
2406
Multimodal parallel attention, Feature parallel,
Spatial parallel, Channel parallel, Medical image segmentation
BibRef
Zhu, E.[Enjun],
Feng, H.[Haiyu],
Chen, L.[Long],
Lai, Y.Q.[Yong-Qiang],
Chai, S.[Senchun],
MP-Net: A Multi-Center Privacy-Preserving Network for Medical Image
Segmentation,
MedImg(43), No. 7, July 2024, pp. 2718-2729.
IEEE DOI
2407
Biomedical imaging, Encryption, Image segmentation, Training, Cryptography,
Hospitals, Medical diagnostic imaging, Deep learning, segmentation
BibRef
Chen, K.[Kecheng],
Qin, T.[Tiexin],
Lee, V.H.F.[Victor Ho-Fun],
Yan, H.[Hong],
Li, H.L.[Hao-Liang],
Learning Robust Shape Regularization for Generalizable Medical Image
Segmentation,
MedImg(43), No. 7, July 2024, pp. 2693-2706.
IEEE DOI
2407
Shape, Image segmentation, Biomedical imaging, Training,
Image edge detection, Feature extraction, knowledge distillation
BibRef
Yang, Z.Y.[Zhi-Yi],
Zhao, Z.[Zhou],
Gu, Y.L.[Yu-Liang],
Xu, Y.C.[Yong-Chao],
Query-guided generalizable medical image segmentation,
PRL(184), 2024, pp. 52-58.
Elsevier DOI
2408
Medical image segmentation, Domain generalized, Query-based transformer
BibRef
Huang, X.R.[Xing-Ru],
Huang, J.[Jian],
Zhao, K.[Kai],
Zhang, T.Y.[Tian-Yun],
Li, Z.[Zhi],
Yue, C.P.[Chang-Peng],
Chen, W.H.[Wen-Hao],
Wang, R.H.[Rui-Hao],
Chen, X.B.[Xuan-Bin],
Zhang, Q.[Qianni],
Fu, Y.[Ying],
Wang, Y.Y.[Yang-Yundou],
Guo, Y.H.[Yi-Hao],
SASAN: Spectrum-Axial Spatial Approach Networks for Medical Image
Segmentation,
MedImg(43), No. 8, August 2024, pp. 3044-3056.
IEEE DOI Code:
WWW Link.
2408
BibRef
Liu, Q.[Qing],
Zeng, H.L.[Hai-Long],
Sun, Z.D.[Zhao-Dong],
Li, X.B.[Xiao-Bai],
Zhao, G.Y.[Guo-Ying],
Liang, Y.X.[Yi-Xiong],
Many birds, one stone: Medical image segmentation with multiple
partially labeled datasets,
PR(155), 2024, pp. 110636.
Elsevier DOI Code:
WWW Link.
2408
Partially supervised learning, Self-training,
Medical image segmentation, Cross-task attention
BibRef
Fiaz, M.[Mustansar],
Noman, M.[Mubashir],
Cholakkal, H.[Hisham],
Anwer, R.M.[Rao Muhammad],
Hanna, J.[Jacob],
Khan, F.S.[Fahad Shahbaz],
Guided-attention and gated-aggregation network for medical image
segmentation,
PR(156), 2024, pp. 110812.
Elsevier DOI Code:
WWW Link.
2408
Medical image segmentation, Multi-scale feature aggregation,
Mask-guided feature attention, Deep supervision, Transformers,
Convolutional neural networks
BibRef
Zhou, T.[Tao],
Zhou, Y.[Yi],
Li, G.Y.[Guang-Yu],
Chen, G.[Geng],
Shen, J.B.[Jian-Bing],
Uncertainty-Aware Hierarchical Aggregation Network for Medical Image
Segmentation,
CirSysVideo(34), No. 8, August 2024, pp. 7440-7453.
IEEE DOI Code:
WWW Link.
2408
Image segmentation, Feature extraction, Biomedical imaging, Semantics,
Fuses, Medical diagnostic imaging, Lesions, scale aggregation module
BibRef
Gai, D.[Di],
Geng, Y.H.[Yu-Han],
Huang, X.[Xia],
Huang, Z.[Zheng],
Xiong, X.[Xin],
Zhou, R.H.[Rui-Hua],
Wang, Q.[Qi],
Feature ensemble network for medical image segmentation with
multi-scale atrous transformer,
IET-IPR(18), No. 11, 2024, pp. 3082-3092.
DOI Link
2409
biomedical imaging, image segmentation, medical image processing
BibRef
Yang, Y.[Yuan],
Zhang, L.[Lin],
Ren, L.[Lei],
Semi-supervised medical image segmentation via cross teaching between
MobileNet and MobileViT,
IVC(150), 2024, pp. 105196.
Elsevier DOI
2409
Segmentation, Semi-supervised learning, MobileViT, Cross teaching
BibRef
Zhao, Z.D.[Zhong-Da],
Wang, H.Y.[Hai-Yan],
Lei, T.[Tao],
Wang, X.[Xuan],
Shen, X.H.[Xiao-Hong],
Yao, H.Y.[Hai-Yang],
Balanced feature fusion collaborative training for semi-supervised
medical image segmentation,
PR(157), 2025, pp. 110856.
Elsevier DOI
2409
Medical image segmentation, Semi-supervised learning, Collaborative training
BibRef
Wang, Y.C.[Yong-Chao],
Xiao, B.[Bin],
Bi, X.L.[Xiu-Li],
Li, W.S.[Wei-Sheng],
Gao, X.B.[Xin-Bo],
Boundary-Aware Prototype in Semi-Supervised Medical Image
Segmentation,
IP(33), 2024, pp. 5456-5467.
IEEE DOI
2410
BibRef
Earlier:
MCF: Mutual Correction Framework for Semi-Supervised Medical Image
Segmentation,
CVPR23(15651-15660)
IEEE DOI
2309
Prototypes, Training, Data models, Biomedical imaging,
Feature extraction, Estimation, Accuracy, Semi-supervised learning,
prototype-based segmentation
BibRef
Wang, Y.[Ying],
Zhang, M.[Meng],
Liang, J.[Jian'an],
Liang, M.Y.[Mei-Yan],
MFH-Net: A Hybrid CNN-Transformer Network Based Multi-Scale Fusion
for Medical Image Segmentation,
IJIST(34), No. 6, 2024, pp. e23192.
DOI Link
2410
medical image segmentation, multi-scale feature fusion,
skip connection, U-Net
BibRef
You, C.Y.[Chen-Yu],
Dai, W.C.[Wei-Cheng],
Liu, F.[Fenglin],
Min, Y.F.[Yi-Fei],
Dvornek, N.C.[Nicha C.],
Li, X.X.[Xiao-Xiao],
Clifton, D.A.[David A.],
Staib, L.[Lawrence],
Duncan, J.S.[James S.],
Mine yOur owN Anatomy: Revisiting Medical Image Segmentation With
Extremely Limited Labels,
PAMI(46), No. 12, December 2024, pp. 11136-11151.
IEEE DOI
2411
Biomedical imaging, Image segmentation, Training,
Contrastive learning, Anatomy, Tail, Image reconstruction,
semi-supervised learning
BibRef
Zhang, Y.M.[Yu-Min],
Li, H.[Hongliu],
Gao, Y.J.[Ya-Jun],
Duan, H.R.[Hao-Ran],
Huang, Y.W.[Ya-Wen],
Zheng, Y.F.[Ye-Feng],
Prototype Correlation Matching and Class- Relation Reasoning for
Few-Shot Medical Image Segmentation,
MedImg(43), No. 11, November 2024, pp. 4041-4054.
IEEE DOI
2411
Medical diagnostic imaging, Image segmentation, Correlation,
Prototypes, Task analysis, Cognition, Semantics,
inter-class relations
BibRef
Huang, W.[Wei],
Zhang, L.[Lei],
Wang, Z.Z.[Zi-Zhou],
Wang, L.[Lituan],
Exploring Inherent Consistency for Semi-Supervised Anatomical
Structure Segmentation in Medical Imaging,
MedImg(43), No. 11, November 2024, pp. 3731-3741.
IEEE DOI
2411
Image segmentation, Anatomical structure, Task analysis,
Biomedical imaging, Data models, Training, Predictive models,
anatomical prior information
BibRef
Chen, T.[Tao],
Wang, C.[Chenhui],
Chen, Z.H.[Zhi-Hao],
Lei, Y.M.[Yi-Ming],
Shan, H.M.[Hong-Ming],
HiDiff: Hybrid Diffusion Framework for Medical Image Segmentation,
MedImg(43), No. 10, October 2024, pp. 3570-3583.
IEEE DOI Code:
WWW Link.
2411
Image segmentation, Biomedical imaging, Diffusion models,
Task analysis, Data models, Training, Transformers,
diffusion model
BibRef
Ji, Z.X.[Ze-Xuan],
Ye, S.L.[Shun-Long],
Ma, X.[Xiao],
Sparse Coding Inspired LSTM and Self-Attention Integration for
Medical Image Segmentation,
IP(33), 2024, pp. 6098-6113.
IEEE DOI Code:
WWW Link.
2411
Long short term memory, Image coding, Image segmentation,
Medical diagnostic imaging, Sparse matrices, Codes,
medical image segmentation
BibRef
Gai, D.[Di],
Wu, Y.X.[Yu-Xuan],
Xiao, Y.S.[Yu-Song],
Geng, Y.H.[Yu-Han],
Cao, L.[Lei],
Xiong, X.[Xin],
Zhong, A.Q.[An-Qi],
Semi-supervised contextual cognitive augmentation-based
cross-teaching network for multiclass medical image segmentation,
IET-IPR(18), No. 13, 2024, pp. 3989-4004.
DOI Link
2411
image processing, medical image processing
BibRef
Zhang, J.W.[Jia-Wei],
Zhang, Y.C.[Yan-Chun],
Qiu, H.L.[Hai-Long],
Wang, T.C.[Tian-Chen],
Li, X.M.[Xiao-Meng],
Zhu, S.F.[Shan-Feng],
Huang, M.P.[Mei-Ping],
Zhuang, J.[Jian],
Shi, Y.Y.[Yi-Yu],
Xu, X.W.[Xiao-Wei],
Constrained multi-scale dense connections for biomedical image
segmentation,
PR(158), 2025, pp. 111031.
Elsevier DOI Code:
WWW Link.
2411
Multi-scale dense connections, Image segmentation,
Network architecture search, Feature fusion
BibRef
Gu, Y.Q.[Yun-Qi],
Zhou, T.[Tao],
Zhang, Y.Z.[Yi-Zhe],
Zhou, Y.[Yi],
He, K.[Kelei],
Gong, C.[Chen],
Fu, H.Z.[Hua-Zhu],
Dual-scale enhanced and cross-generative consistency learning for
semi-supervised medical image segmentation,
PR(158), 2025, pp. 110962.
Elsevier DOI Code:
WWW Link.
2411
Medical image segmentation, Semi-supervised learning,
Scale-enhanced consistency, Cross-generative consistency
BibRef
Sun, J.D.[Jun-Ding],
Li, Y.[Yabei],
Wu, X.S.[Xiao-Sheng],
Tang, C.[Chaosheng],
Wang, S.H.[Shui-Hua],
Zhang, Y.D.[Yu-Dong],
HAD-Net: An attention U-based network with hyper-scale shifted
aggregating and max-diagonal sampling for medical image segmentation,
CVIU(249), 2024, pp. 104151.
Elsevier DOI
2412
Medical image segmentation, Max-diagonal pooling,
Channel-space attention, Hyper-scale shifted aggregation
BibRef
Ning, G.J.[Gang-Jun],
Liu, P.P.[Ping-Ping],
Dai, C.Y.[Chuang-Ye],
Sun, M.[Mingsi],
Zhou, Q.Z.[Qiu-Zhan],
Li, Q.L.[Qing-Liang],
RGAM: A refined global attention mechanism for medical image
segmentation,
IET-CV(18), No. 8, 2024, pp. 1362-1375.
DOI Link
2501
convolutional neural nets, medical image processing
BibRef
Zhang, Z.[Zheng],
Yin, G.C.[Guan-Chun],
Ma, Z.[Zibo],
Tan, Y.P.[Yun-Peng],
Zhang, B.[Bo],
Zhuang, Y.F.[Yu-Feng],
IDA-NET: Individual Difference aware Medical Image Segmentation with
Meta-Learning,
PRL(187), 2025, pp. 21-27.
Elsevier DOI
2501
Transformer, U-Net, Meta Learning, Individual Difference,
Medical Image Segmentation
BibRef
Gao, J.[Jun],
Lao, Q.[Qicheng],
Kang, Q.B.[Qing-Bo],
Liu, P.[Paul],
Du, C.L.[Chen-Lin],
Li, K.[Kang],
Zhang, L.[Le],
Boosting Your Context by Dual Similarity Checkup for In-Context
Learning Medical Image Segmentation,
MedImg(44), No. 1, January 2025, pp. 310-319.
IEEE DOI
2501
Image segmentation, Biomedical imaging, Task analysis, Semantics,
Visualization, Data models, Computational modeling,
support set reinforcement
BibRef
Amaan-Valiuddin, M.M.,
Viviers, C.G.A.[Christiaan G. A.],
van Sloun, R.J.G.[Ruud J. G.],
de With, P.H.N.[Peter H. N.],
van der Sommen, F.[Fons],
Investigating and Improving Latent Density Segmentation Models for
Aleatoric Uncertainty Quantification in Medical Imaging,
MedImg(44), No. 1, January 2025, pp. 384-395.
IEEE DOI
2501
Uncertainty, Image segmentation, Probabilistic logic, Decoding,
Training, Biomedical imaging, Annotations,
latent density modeling
BibRef
Huang, W.D.[Wen-Dong],
Hu, J.[Jinwu],
Xiao, J.H.[Jun-Hao],
Wei, Y.[Yang],
Bi, X.L.[Xiu-Li],
Xiao, B.[Bin],
Prototype-Guided Graph Reasoning Network for Few-Shot Medical Image
Segmentation,
MedImg(44), No. 2, February 2025, pp. 761-773.
IEEE DOI
2502
Prototypes, Semantic segmentation, Cognition,
Medical diagnostic imaging, Training, Data models,
medical image segmentation
BibRef
Chen, Y.Z.[Yun-Zhu],
Liu, Y.[Yang],
Lu, M.[Manti],
Fu, L.[Liyao],
Yang, F.[Feng],
Multi-consistency for semi-supervised medical image segmentation via
diffusion models,
PR(161), 2025, pp. 111216.
Elsevier DOI Code:
WWW Link.
2502
Medical image segmentation, Diffusion models, Semi-supervised learning
BibRef
Dhamale, A.[Akshat],
Rajalakshmi, R.[Ratnavel],
Balasundaram, A.[Ananthakrishnan],
Dual multi scale networks for medical image segmentation using
contrastive learning,
IVC(154), 2025, pp. 105371.
Elsevier DOI
2502
Contrastive learning, Multi-scale architecture,
Encoder-decoder based model, Medical image segmentation
BibRef
Wang, W.[Wei],
He, J.X.[Ji-Xing],
Wang, X.[Xin],
Rethinking Feature Guidance for Medical Image Segmentation,
SPLetters(32), 2025, pp. 641-645.
IEEE DOI
2502
Feature extraction, Image segmentation, Lesions,
Medical diagnostic imaging, Convolution, Logic gates, Transformers,
medical image segmentation
BibRef
Huang, S.[Senlong],
Ge, Y.X.[Yong-Xin],
Liu, D.F.[Dong-Fang],
Hong, M.J.[Ming-Jian],
Zhao, J.[Junhan],
Loui, A.C.[Alexander C.],
Rethinking Copy-Paste for Consistency Learning in Medical Image
Segmentation,
IP(34), 2025, pp. 1060-1074.
IEEE DOI Code:
WWW Link.
2502
Perturbation methods, Data models, Training, Image segmentation,
Medical diagnostic imaging, Uncertainty, Estimation, Training data,
copy-paste
BibRef
Huang, Y.Z.[Yun-Zhi],
Han, L.[Luyi],
Dou, H.R.[Hao-Ran],
Generative feature style augmentation for domain generalization in
medical image segmentation,
PR(162), 2025, pp. 111416.
Elsevier DOI
2503
Domain generalization, Variation inference, Feature style mapping
BibRef
Ren, Z.T.[Zi-Tong],
Li, Y.M.[Yong-Ming],
Wang, L.J.[Lie-Jun],
Xu, L.H.[Liang-Hui],
Lite-MixedNet: Lightweight and efficient hybrid network for medical
image segmentation,
PR(162), 2025, pp. 111378.
Elsevier DOI Code:
WWW Link.
2503
Medical image segmentation, Convolutional Neural Network,
Vision Transformer, Self-attention mechanism
BibRef
Wang, Z.H.[Zhi-Hua],
He, Y.X.[Yu-Xin],
Yi, Z.[Zhang],
He, T.[Tao],
Bu, J.J.[Jia-Jun],
Neural Memory Self-Supervised State Space Models With Learnable Gates,
SPLetters(32), 2025, pp. 926-930.
IEEE DOI
2503
Computational modeling, Logic gates, Image segmentation, Decoding,
Training, Image reconstruction, Head, Biomedical imaging,
self-supervision
BibRef
Xie, B.[Bin],
Tang, H.[Hao],
Cai, D.[Dawen],
Yan, Y.[Yan],
MS-UMLP: Medical Image Segmentation via Multi-scale U-shape Mlp-mixer,
ACCV24(X: 325-341).
Springer DOI
2412
BibRef
Tian, Y.[Yu],
Wen, C.C.[Cong-Cong],
Shi, M.[Min],
Afzal, M.M.[Muhammad Muneeb],
Huang, H.[Hao],
Khan, M.O.[Muhammad Osama],
Luo, Y.[Yan],
Fang, Y.[Yi],
Wang, M.Y.[Meng-Yu],
Fairdomain: Achieving Fairness in Cross-domain Medical Image
Segmentation and Classification,
ECCV24(LXXVI: 251-271).
Springer DOI
2412
BibRef
Xu, C.[Chen],
Huang, Q.M.[Qi-Ming],
Hou, Y.Q.[Yu-Qi],
Wu, J.X.[Jiang-Xing],
Zhang, F.[Fan],
Chang, H.J.[Hyung Jin],
Jiao, J.B.[Jian-Bo],
Few Exemplar-based General Medical Image Segmentation via Domain-aware
Selective Adaptation,
ACCV24(II: 159-173).
Springer DOI
2412
BibRef
Liu, Y.F.[Yu-Fan],
Wang, Z.Y.[Zi-Yang],
Chen, T.X.[Tian-Xiang],
Ye, Z.[Zi],
Quadruple-Consistency Vision Transformer for Medical Image
Segmentation with Limited Number of Sparse Annotations,
ICIP24(2101-2107)
IEEE DOI Code:
WWW Link.
2411
Training, Measurement, Image segmentation, Annotations,
Perturbation methods, Supervised learning,
Semi-Supervised Learning
BibRef
Khan, T.M.[Tariq M],
Iqbal, S.[Shahzaib],
Naqvi, S.S.[Syed S.],
Razzak, I.[Imran],
Meijering, E.[Erik],
LMBF-Net: A Lightweight Multipath Bidirectional Focal Attention
Network for Multifeatures Segmentation,
ICIP24(2807-2813)
IEEE DOI
2411
Optical filters, Integrated optics, Image segmentation,
Convolution, Modulation, Optical fiber networks, Optical imaging,
Medical Image Segmentation
BibRef
Du, Q.Y.[Qian-Yu],
Zhong, B.J.[Bao-Jiang],
Ma, K.K.[Kai-Kuang],
ATU-NET: An Adaptive Transformation-Based U-NET for Medical Image
Segmentation,
ICIP24(2989-2995)
IEEE DOI
2411
Training, Image segmentation, Adaptive systems, Transforms,
Network architecture, Benchmark testing, Feature extraction,
encoder-decoder architecture
BibRef
Wu, J.[Junde],
Xu, M.[Min],
One-Prompt to Segment All Medical Images,
CVPR24(11302-11312)
IEEE DOI Code:
WWW Link.
2410
Learning systems, Image segmentation, Adaptation models,
Visualization, Costs, Computational modeling
BibRef
Perera, S.[Shehan],
Navard, P.[Pouyan],
Yilmaz, A.[Alper],
SegFormer3D: an Efficient Transformer for 3D Medical Image
Segmentation,
DEF-AI-MIA24(4981-4988)
IEEE DOI Code:
WWW Link.
2410
Training, Image segmentation, Solid modeling, Computational modeling,
Computer architecture, Transformers, Deep Learning
BibRef
Ding, Y.H.[Yu-Hang],
Li, L.[Liulei],
Wang, W.G.[Wen-Guan],
Yang, Y.[Yi],
Clustering Propagation for Universal Medical Image Segmentation,
CVPR24(3357-3369)
IEEE DOI
2410
Training, Knowledge engineering, Image segmentation,
Solid modeling, Image coding
BibRef
Cheng, Z.H.[Zhi-Heng],
Wei, Q.Y.[Qing-Yue],
Zhu, H.[Hongru],
Wang, Y.[Yan],
Qu, L.Q.[Liang-Qiong],
Shao, W.[Wei],
Zhou, Y.[Yuyin],
Unleashing the Potential of SAM for Medical Adaptation via
Hierarchical Decoding,
CVPR24(3511-3522)
IEEE DOI Code:
WWW Link.
2410
Training, Image segmentation, Adaptation models, Costs,
Training data, Probabilistic logic, Data models,
medical image segmentation
BibRef
Rakic, M.[Marianne],
Wong, H.E.[Hallee E.],
Ortiz, J.J.G.[Jose Javier Gonzalez],
Cimini, B.A.[Beth A.],
Guttag, J.V.[John V.],
Dalca, A.V.[Adrian V.],
Tyche: Stochastic in-Context Learning for Medical Image Segmentation,
CVPR24(11159-11173)
IEEE DOI Code:
WWW Link.
2410
Training, Learning systems, Image segmentation, Uncertainty,
Convolution, Stochastic processes, Machine learning, uncertainty,
medical imaging
BibRef
Chen, Z.Y.[Zi-Yang],
Pan, Y.S.[Yong-Sheng],
Ye, Y.W.[Yi-Wen],
Lu, M.K.[Meng-Kang],
Xia, Y.[Yong],
Each Test Image Deserves A Specific Prompt: Continual Test-Time
Adaptation for 2D Medical Image Segmentation,
CVPR24(11184-11193)
IEEE DOI Code:
WWW Link.
2410
Training, Adaptation models, Visualization, Codes,
Semantic segmentation, Benchmark testing
BibRef
Wu, Y.C.[Yi-Cheng],
Luo, X.[Xiangde],
Xu, Z.[Zhe],
Guo, X.Q.[Xiao-Qing],
Ju, L.[Lie],
Ge, Z.Y.[Zong-Yuan],
Liao, W.J.[Wen-Jun],
Cai, J.F.[Jian-Fei],
Diversified and Personalized Multi-Rater Medical Image Segmentation,
CVPR24(11470-11479)
IEEE DOI Code:
WWW Link.
2410
Training, Image segmentation, Adaptation models, Codes, Uncertainty,
Annotations, Computational modeling
BibRef
Chen, X.Y.[Xiao-Yang],
Zheng, H.[Hao],
Li, Y.M.[Yue-Meng],
Ma, Y.C.[Yun-Cong],
Ma, L.[Liang],
Li, H.M.[Hong-Ming],
Fan, Y.[Yong],
Versatile Medical Image Segmentation Learned from Multi-Source
Datasets via Model Self-Disambiguation,
CVPR24(11747-11756)
IEEE DOI
2410
Training, Image segmentation, Solid modeling, Protocols, Annotations,
Prevention and mitigation, Computational modeling
BibRef
Dong, H.Y.[Hao-Yu],
Konz, N.[Nicholas],
Gu, H.[Hanxue],
Mazurowski, M.A.[Maciej A.],
Medical Image Segmentation with InTEnt: Integrated Entropy Weighting
for Single Image Test-Time Adaptation,
DEF-AI-MIA24(5046-5055)
IEEE DOI
2410
Training, Image segmentation, Adaptation models, Estimation,
Predictive models, Nonhomogeneous media, Entropy,
test-time adaptation
BibRef
Aleem, S.[Sidra],
Wang, F.[Fangyijie],
Maniparambil, M.[Mayug],
Arazo, E.[Eric],
Dietlmeier, J.[Julia],
Curran, K.[Kathleen],
O'Connor, N.E.[Noel E.],
Little, S.[Suzanne],
Test-Time Adaptation with SaLIP: A Cascade of SAM and CLIP for
Zero-shot Medical Image Segmentation,
DEF-AI-MIA24(5184-5193)
IEEE DOI
2410
Image segmentation, Adaptation models, Filtering,
Inference mechanisms, Lung, Robustness, Pattern recognition
BibRef
Nam, J.H.[Ju-Hyeon],
Syazwany, N.S.[Nur Suriza],
Kim, S.J.[Su Jung],
Lee, S.C.[Sang-Chul],
Modality-Agnostic Domain Generalizable Medical Image Segmentation by
Multi-Frequency in Multi-Scale Attention,
CVPR24(11480-11491)
IEEE DOI
2410
Image segmentation, Image analysis, Frequency-domain analysis,
Feature extraction, Data mining, Noise measurement, Image Segmentation
BibRef
Schmidt-Mengin, M.[Marius],
Benichoux, A.[Alexis],
Belachew, S.[Shibeshih],
Komodakis, N.[Nikos],
Paragios, N.[Nikos],
ToNNO: Tomographic Reconstruction of a Neural Network's Output for
Weakly Supervised Segmentation of 3D Medical Images,
CVPR24(11428-11438)
IEEE DOI
2410
Training, Solid modeling, Semantic segmentation, Transforms,
Tomography, Pattern recognition
BibRef
Li, Z.[Zhe],
Yang, L.T.[Laurence T.],
Ren, B.[Bocheng],
Nie, X.[Xin],
Gao, Z.Y.[Zhang-Yang],
Tan, C.[Cheng],
Li, S.Z.[Stan Z.],
MLIP: Enhancing Medical Visual Representation with Divergence Encoder
and Knowledge-guided Contrastive Learning,
CVPR24(11704-11714)
IEEE DOI Code:
WWW Link.
2410
Representation learning, Visualization, Semantic segmentation,
Contrastive learning, Object detection, Pattern recognition
BibRef
Azad, R.[Reza],
Niggemeier, L.[Leon],
Hüttemann, M.[Michael],
Kazerouni, A.[Amirhossein],
Aghdam, E.K.[Ehsan Khodapanah],
Velichko, Y.[Yury],
Bagci, U.[Ulas],
Merhof, D.[Dorit],
Beyond Self-Attention: Deformable Large Kernel Attention for Medical
Image Segmentation,
WACV24(1276-1286)
IEEE DOI
2404
Image segmentation, Adaptation models, Convolution,
Computational modeling, Transformers, Data models, Algorithms,
Biomedical / healthcare / medicine
BibRef
Rahman, M.M.[Md Motiur],
Shokouhmand, S.[Shiva],
Bhatt, S.[Smriti],
Faezipour, M.[Miad],
MIST: Medical Image Segmentation Transformer with Convolutional
Attention Mixing (CAM) Decoder,
WACV24(403-412)
IEEE DOI
2404
Convolutional codes, Image segmentation, Computational modeling,
Semantics, Transformers, Decoding, Kernel, Algorithms,
Biomedical / healthcare / medicine
BibRef
Leng, T.[Tianang],
Zhang, Y.M.[Yi-Ming],
Han, K.[Kun],
Xie, X.H.[Xiao-Hui],
Self-Sampling Meta SAM: Enhancing Few-shot Medical Image Segmentation
with Meta-Learning,
WACV24(7910-7920)
IEEE DOI Code:
WWW Link.
2404
Training, Metalearning, Image segmentation, Adaptation models,
Visualization, Technological innovation, Training data
BibRef
Gorade, V.[Vandan],
Mittal, S.[Sparsh],
Jha, D.[Debesh],
Bagci, U.[Ulas],
SynergyNet: Bridging the Gap between Discrete and Continuous
Representations for Precise Medical Image Segmentation,
WACV24(7753-7762)
IEEE DOI
2404
Deep learning, Image segmentation, Analytical models,
Image analysis, Computer architecture, Skin, Applications,
Image recognition and understanding
BibRef
Schmidt, A.[Arne],
Morales-Álvarez, P.[Pablo],
Molina, R.[Rafael],
Probabilistic Modeling of Inter- and Intra-observer Variability in
Medical Image Segmentation,
ICCV23(21040-21049)
IEEE DOI
2401
BibRef
Singh, P.[Pranav],
Chen, L.[Luoyao],
Chen, M.[Mei],
Pan, J.Q.[Jin-Qian],
Chukkapalli, R.[Raviteja],
Chaudhari, S.[Shravan],
Cirrone, J.[Jacopo],
Enhancing Medical Image Segmentation: Optimizing Cross-Entropy
Weights and Post-Processing with Autoencoders,
CVAMD23(2676-2685)
IEEE DOI
2401
BibRef
Pandey, S.[Sumit],
Chen, K.F.[Kuan-Fu],
Dam, E.B.[Erik B.],
Comprehensive Multimodal Segmentation in Medical Imaging:
Combining YOLOv8 with SAM and HQ-SAM Models,
CVAMD23(2584-2590)
IEEE DOI
2401
BibRef
Pal, D.[Debojyoti],
Meena, T.[Tanushree],
Mahapatra, D.[Dwarikanath],
Roy, S.[Sudipta],
AW-Net: A Novel Fully Connected Attention-based Medical Image
Segmentation Model,
CVAMD23(2524-2533)
IEEE DOI Code:
WWW Link.
2401
BibRef
Bastico, M.[Matteo],
Ryckelynck, D.[David],
Corté, L.[Laurent],
Tillier, Y.[Yannick],
Decencière, E.[Etienne],
A Simple and Robust Framework for Cross-Modality Medical Image
Segmentation applied to Vision Transformers,
LXCV-ICCV23(4130-4140)
IEEE DOI Code:
WWW Link.
2401
BibRef
Butoi, V.I.[Victor Ion],
Ortiz, J.J.G.[Jose Javier Gonzalez],
Ma, T.Y.[Tian-Yu],
Sabuncu, M.R.[Mert R.],
Guttag, J.[John],
Dalca, A.V.[Adrian V.],
UniverSeg: Universal Medical Image Segmentation,
ICCV23(21381-21394)
IEEE DOI Code:
WWW Link.
2401
BibRef
Marinov, Z.[Zdravko],
Reiß, S.[Simon],
Kersting, D.[David],
Kleesiek, J.[Jens],
Stiefelhagen, R.[Rainer],
Mirror U-Net: Marrying Multimodal Fission with Multi-task Learning
for Semantic Segmentation in Medical Imaging,
CVAMD23(2275-2285)
IEEE DOI Code:
WWW Link.
2401
BibRef
Hu, H.[Haigen],
Jin, Z.C.[Zhi-Chao],
Zhou, Q.W.[Qian-Wei],
Guan, Q.[Qiu],
Chen, Q.[Qi],
CTI-Unet: Hybrid Local Features and Global Representations
Efficiently,
ICIP23(735-739)
IEEE DOI Code:
WWW Link.
2312
BibRef
Li, J.Q.[Jiu-Qiang],
MCTE: Marrying Convolution and Transformer Efficiently for End-to-End
Medical Image Segmentation,
ICIP23(1100-1104)
IEEE DOI
2312
BibRef
Huang, Y.[Yao],
Liu, J.M.[Jian-Ming],
Chen, H.[Hua],
Self-Reinforcing For Few-Shot Medical Image Segmentation,
ICIP23(655-659)
IEEE DOI Code:
WWW Link.
2312
BibRef
Jiang, M.R.[Mei-Rui],
Roth, H.R.[Holger R.],
Li, W.Q.[Wen-Qi],
Yang, D.[Dong],
Zhao, C.[Can],
Nath, V.[Vishwesh],
Xu, D.G.[Da-Guang],
Dou, Q.[Qi],
Xu, Z.Y.[Zi-Yue],
Fair Federated Medical Image Segmentation via Client Contribution
Estimation,
CVPR23(16302-16311)
IEEE DOI
2309
BibRef
Bai, Y.H.[Yun-Hao],
Chen, D.[Duowen],
Li, Q.L.[Qing-Li],
Shen, W.[Wei],
Wang, Y.[Yan],
Bidirectional Copy-Paste for Semi-Supervised Medical Image
Segmentation,
CVPR23(11514-11524)
IEEE DOI
2309
BibRef
Rahman, A.[Aimon],
Valanarasu, J.M.J.[Jeya Maria Jose],
Hacihaliloglu, I.[Ilker],
Patel, V.M.[Vishal M.],
Ambiguous Medical Image Segmentation Using Diffusion Models,
CVPR23(11536-11546)
IEEE DOI
2309
BibRef
Basak, H.[Hritam],
Yin, Z.Z.[Zhao-Zheng],
Pseudo-Label Guided Contrastive Learning for Semi-Supervised Medical
Image Segmentation,
CVPR23(19786-19797)
IEEE DOI
2309
BibRef
Santhirasekaram, A.[Ainkaran],
Winkler, M.[Mathias],
Rockall, A.[Andrea],
Glocker, B.[Ben],
Topology Preserving Compositionality for Robust Medical Image
Segmentation,
TAG-PRA23(543-552)
IEEE DOI
2309
BibRef
Yuan, M.Z.[Ming-Ze],
Xia, Y.[Yingda],
Dong, H.X.[He-Xin],
Chen, Z.[Zifan],
Yao, J.[Jiawen],
Qiu, M.Y.[Ming-Yan],
Yan, K.[Ke],
Yin, X.L.[Xiao-Li],
Shi, Y.[Yu],
Chen, X.[Xin],
Liu, Z.[Zaiyi],
Dong, B.[Bin],
Zhou, J.[Jingren],
Lu, L.[Le],
Zhang, L.[Ling],
Zhang, L.[Li],
Devil is in the Queries: Advancing Mask Transformers for Real-world
Medical Image Segmentation and Out-of-Distribution Localization,
CVPR23(23879-23889)
IEEE DOI
2309
BibRef
Jeong, S.W.[Seung-Wan],
Cho, H.H.[Hwan-Ho],
Kwon, J.[Junmo],
Park, H.[Hyunjin],
Region-of-interest Attentive Heteromodal Variational Encoder-decoder
for Segmentation with Missing Modalities,
ACCV22(VI:132-148).
Springer DOI
2307
BibRef
Zheng, Z.[Zhou],
Hayashi, Y.[Yuichiro],
Oda, M.[Masahiro],
Kitasaka, T.[Takayuki],
Mori, K.[Kensaku],
Trimix: A General Framework for Medical Image Segmentation from Limited
Supervision,
ACCV22(VI:185-202).
Springer DOI
2307
BibRef
Tian, M.[Mu],
Yang, Q.[Qinzhu],
Gao, Y.[Yi],
Multi-scale Multi-task Distillation for Incremental 3d Medical Image
Segmentation,
MCV22(369-384).
Springer DOI
2304
BibRef
Salpea, N.[Natalia],
Tzouveli, P.[Paraskevi],
Kollias, D.[Dimitrios],
Medical Image Segmentation: A Review of Modern Architectures,
MIA-COVID19D22(691-708).
Springer DOI
2304
BibRef
Wang, Z.Y.[Zi-Yang],
Li, T.Z.[Tian-Ze],
Zheng, J.Q.[Jian-Qing],
Huang, B.[Baoru],
When CNN Meet with VIT: Towards Semi-supervised Learning for
Multi-class Medical Image Semantic Segmentation,
MIA-COVID19D22(424-441).
Springer DOI
2304
BibRef
Tragakis, A.[Athanasios],
Kaul, C.[Chaitanya],
Murray-Smith, R.[Roderick],
Husmeier, D.[Dirk],
The Fully Convolutional Transformer for Medical Image Segmentation,
WACV23(3649-3658)
IEEE DOI
2302
Convolutional codes, Image segmentation,
Technological innovation, Semantic segmentation, Semantics,
Applications: Biomedical/healthcare/medicine
BibRef
Heidari, M.[Moein],
Kazerouni, A.[Amirhossein],
Soltany, M.[Milad],
Azad, R.[Reza],
Aghdam, E.K.[Ehsan Khodapanah],
Cohen-Adad, J.[Julien],
Merhof, D.[Dorit],
HiFormer: Hierarchical Multi-scale Representations Using Transformers
for Medical Image Segmentation,
WACV23(6191-6201)
IEEE DOI
2302
Image segmentation, Correlation, Convolution,
Computational modeling, Transformers, Biomedical/healthcare/medicine
BibRef
Rahman, M.M.[Md Mostafijur],
Munir, M.[Mustafa],
Marculescu, R.[Radu],
EMCAD: Efficient Multi-Scale Convolutional Attention Decoding for
Medical Image Segmentation,
CVPR24(11769-11779)
IEEE DOI Code:
WWW Link.
2410
Image segmentation, Convolution, Semantic segmentation,
Point of care, Logic gates, Decoding, Computational efficiency,
Medical Image Segmentation
BibRef
Rahman, M.M.[Md Mostafijur],
Marculescu, R.[Radu],
G-CASCADE: Efficient Cascaded Graph Convolutional Decoding for 2D
Medical Image Segmentation,
WACV24(7713-7722)
IEEE DOI Code:
WWW Link.
2404
BibRef
Earlier:
Medical Image Segmentation via Cascaded Attention Decoding,
WACV23(6211-6220)
IEEE DOI
2302
Image segmentation, Convolution, Semantic segmentation, Semantics,
Transformers, Skin, Decoding, Applications, and algorithms.
Medical services, Logic gates, Lesions: Biomedical/healthcare/medicine
BibRef
Cho, W.W.[Won-Woo],
Park, J.[Jeonghoon],
Choo, J.[Jaegul],
Training Auxiliary Prototypical Classifiers for Explainable Anomaly
Detection in Medical Image Segmentation,
WACV23(2623-2632)
IEEE DOI
2302
Training, Image segmentation, Machine learning algorithms,
Pipelines, Training data, Network architecture, Data processing,
visual reasoning
BibRef
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Image segmentation, Convolution, Frequency-domain analysis,
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Deep learning, Image segmentation, Image resolution, Convolution,
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Knowledge engineering, Image segmentation, Limiting,
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Image segmentation, Semantics,
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Deep learning, Image segmentation, Sensitivity,
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Biomedical imaging, Generators, Data privacy,
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convolutional neural nets, graph theory, image representation,
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CVPR18(8300-8308)
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1812
Quantization (signal), Training, Biomedical imaging,
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Kromp, F.,
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Machine learning framework incorporating expert knowledge in tissue
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ICPR16(343-348)
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1705
Algorithm design and analysis, Biological tissues,
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ICIP17(3280-3284)
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Markov processes, biomedical MRI, diseases, image registration,
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Biomedical Imaging
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0509
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Earlier:
Medical image segmentation using the watershed transformation on graphs,
ICIP96(III: 37-40).
IEEE DOI
9610
Image Segmentation for a Hyperthermia Planning Environment
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Wegner, S.,
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BibRef
Chapter on 2-D Region Segmentation Techniques, Snakes, Active Contours continues in
Weakly Supervised, Self Supervised Semantic Segmentation .