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Glands, Image segmentation, Semantics, Feature extraction,
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2201
Training, Deep learning, Pathology, Microorganisms, Protocols, Oils,
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2201
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2112
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CVAMD21(3402-3408)
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2112
Visualization, Pathology, Computer architecture,
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CDPath21(664-673)
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2112
Codes, Histopathology, Topology, Task analysis, Tumors
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CDPath21(674-683)
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2112
Geometry, Deep learning, Image segmentation, Histopathology,
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CDPath21(648-656)
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2112
Visualization, Histopathology, Pipelines,
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CDPath21(639-647)
IEEE DOI
2112
Visualization, Codes, Histopathology,
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Joint Semi-supervised and Active Learning for Segmentation of
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CDPath21(591-600)
IEEE DOI
2112
Training, Deep learning, Pathology, Image segmentation,
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H&E-adversarial network: a convolutional neural network to learn
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CDPath21(601-610)
IEEE DOI
2112
Training, Image segmentation, Image color analysis, Histopathology,
Neural networks, Convolutional neural networks
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An investigation of attention mechanisms in histopathology
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CDPath21(611-619)
IEEE DOI
2112
Analytical models, Histopathology,
Computational modeling, Focusing, Predictive models
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Firmbach, D.[Daniel],
Geppert, C.I.[Carol I.],
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Bruns, V.[Volker],
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Perrin, D.[Dominik],
Wittenberg, T.[Thomas],
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Multi-Prototype Few-shot Learning in Histopathology,
CDPath21(620-628)
IEEE DOI
2112
Training, Degradation, Histopathology, Neural networks,
Prototypes, Distributed databases
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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
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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
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Gamper, J.[Jevgenij],
Rajpoot, N.[Nasir],
Multiple Instance Captioning: Learning Representations from
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CVPR21(16544-16554)
IEEE DOI
2111
Histopathology, Computational modeling,
Estimation, Pattern recognition, Task analysis
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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, Pattern recognition
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tepec, D.[Dejan],
Skocaj, D.[Danijel],
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],
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
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Belharbi, S.[Soufiane],
Ben Ayed, I.[Ismail],
McCaffrey, L.[Luke],
Granger, E.[Eric],
Deep Active Learning for Joint Classification Segmentation with Weak
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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],
Chen, S.[Shuyan],
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
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MMMod21(II:87-98).
Springer DOI
2106
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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.[Yiwen],
Zhou, X.G.[Xiao-Guang],
Sun, M.[Muyi],
Zhang, G.[Guanhong],
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
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Shin, B.[Beomjo],
Cho, J.[Junsu],
Yu, H.[Hwanjo],
Choi, S.J.[Seung-Jin],
Sparse Network Inversion for Key Instance Detection in Multiple
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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],
Aksoy, S.[Selim],
Kösemehmetoglu, K.[Kemal],
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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],
Karray, F.[Fakhri],
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ICPR21(7080-7086)
IEEE DOI
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Training, Histopathology, Training data, Stochastic processes,
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ICIP20(360-364)
IEEE DOI
2011
Image color analysis, Image reconstruction,
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CRV20(101-108)
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IPTA17(1-6)
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1804
feature extraction, image classification, image representation,
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BioIm17(27-35)
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Biological system modeling, Feature extraction, Histograms,
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ICIP17(3075-3079)
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Diseases, Image color analysis, Image segmentation,
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IPTA16(1-6)
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ICIP15(2060-2064)
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IPTA14(1-6)
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ICIP14(3953-3957)
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Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Fluorescence Analysis, Microscopic Analysis, Cells .