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Elsevier DOI
0902
Whole-slide histopathological image analysis; Texture analysis; Neuroblastoma
BibRef
Kong, J.[Jun],
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Shimada, H.[Hiroyuki],
Boyer, K.L.[Kim L.],
Saltz, J.[Joel],
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Computer-aided evaluation of neuroblastoma on whole-slide histology
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Elsevier DOI
0902
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Earlier:
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IEEE DOI
0709
Quantitative image analysis; Microscopy images; Neuroblastoma
prognosis; Grade of differentiation; Multi-resolution pathological
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BibRef
Zhu, S.J.[Shu-Jin],
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Elsevier DOI
1809
Image retrieval, Image representation, Histopathology,
Wholeslide imaging, Bag-of-words, Dictionary learning, LBP, SVM, Deep learning
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Yu, Y.B.[Yong-Bin],
Cai, J.Y.[Jing-Ye],
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artificial intelligence, capsule network, colon cancer,
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BibRef
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DSNet: A Dual-Stream Framework for Weakly-Supervised Gigapixel
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MedImg(41), No. 8, August 2022, pp. 2180-2190.
IEEE DOI
2208
Visualization, Encoding, Annotations, Redundancy, Pathology,
Metastasis, Image analysis, Weakly-supervised training,
whole slide images
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Zheng, Y.[Yi],
Gindra, R.H.[Rushin H.],
Green, E.J.[Emily J.],
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Betke, M.[Margrit],
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Kolachalama, V.B.[Vijaya B.],
A Graph-Transformer for Whole Slide Image Classification,
MedImg(41), No. 11, November 2022, pp. 3003-3015.
IEEE DOI
2211
Pathology, Feature extraction, Transformers, Tumors, Deep learning,
Training, Lung, Digital pathology, graph convolutional network,
lung cancer
BibRef
Wang, Z.Z.[Zhen-Zhen],
Saoud, C.[Carla],
Wangsiricharoen, S.[Sintawat],
James, A.W.[Aaron W.],
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Label Cleaning Multiple Instance Learning: Refining Coarse
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MedImg(41), No. 12, December 2022, pp. 3952-3968.
IEEE DOI
2212
Annotations, Cancer, Pathology, Training, Tumors, Refining,
Predictive models, Whole-slide image segmentation, label cleaning
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Jiang, Y.H.[Ying-Hai],
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Liu, F.[Feng],
Multi-resolutional human visual perception optimized pathology image
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SP:IC(115), 2023, pp. 116960.
Elsevier DOI
2306
Image coding, Multi-resolution, JPEG2000, Perception-based image quality,
Visibility threshold, Whole-slide pathology image
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Wu, Z.[Zihao],
Ming, Y.[Yu],
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IEEE DOI
2306
Federated learning, Bayes methods, Pathology, Training,
Probabilistic logic, Task analysis, Graphics processing units,
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Huai, J.G.[Jian-Guo],
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Kernel Attention Transformer for Histopathology Whole Slide Image
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IEEE DOI
2310
BibRef
Wang, Z.[Zhao],
Feng, Q.Y.[Qian-Yu],
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Elsevier DOI
2310
Image segmentation, Evaluation metric, Histology image
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Shared-Specific Feature Learning With Bottleneck Fusion Transformer
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MedImg(42), No. 11, November 2023, pp. 3374-3383.
IEEE DOI
2311
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Morales-Álvarez, P.[Pablo],
Schmidt, A.[Arne],
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Introducing instance label correlation in multiple instance learning.
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Elsevier DOI
2311
Multiple instance learning, Gaussian processes, Ising model,
Variational inference, Whole slide images, Histopathology
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Shi, J.B.[Jiang-Bo],
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Gao, Z.[Zeyu],
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MG-Trans: Multi-Scale Graph Transformer With Information Bottleneck
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IEEE DOI
2312
BibRef
Fang, K.[Kun],
Jia, J.J.[Jing-Jing],
A whole-slide pathology segmentation framework for the diagnosis of
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CVIDL23(310-313)
IEEE DOI
2403
Deep learning, Training, Image segmentation, Pathology,
Statistical analysis, Biopsy, Lung cancer, Whole slide image,
Image classification
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Qu, L.H.[Lin-Hao],
Yang, Z.W.[Zhi-Wei],
Duan, M.H.[Ming-Hong],
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Boosting Whole Slide Image Classification from the Perspectives of
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ICCV23(21406-21416)
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2401
BibRef
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LNPL-MIL: Learning from Noisy Pseudo Labels for Promoting Multiple
Instance Learning in Whole Slide Image,
ICCV23(21438-21438)
IEEE DOI
2401
BibRef
Tang, W.H.[Wen-Hao],
Huang, S.[Sheng],
Zhang, X.X.[Xiao-Xian],
Zhou, F.T.[Feng-Tao],
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Multiple Instance Learning Framework with Masked Hard Instance Mining
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ICCV23(4055-4064)
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WWW Link.
2401
BibRef
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ConSlide: Asynchronous Hierarchical Interaction Transformer with
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ICCV23(21292-21303)
IEEE DOI
2401
BibRef
Chan, T.H.[Tsai Hor],
Cendra, F.J.[Fernando Julio],
Ma, L.[Lan],
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Histopathology Whole Slide Image Analysis with Heterogeneous Graph
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CVPR23(15661-15670)
IEEE DOI
2309
BibRef
Lin, T.C.[Tian-Cheng],
Yu, Z.M.[Zhi-Miao],
Hu, H.Y.[Hong-Yu],
Xu, Y.[Yi],
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Interventional Bag Multi-Instance Learning On Whole-Slide
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CVPR23(19830-19839)
IEEE DOI
2309
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Chen, Y.C.[Yuan-Chih],
Lu, C.S.[Chun-Shien],
RankMix: Data Augmentation for Weakly Supervised Learning of
Classifying Whole Slide Images with Diverse Sizes and Imbalanced
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CVPR23(23936-23945)
IEEE DOI
2309
BibRef
Li, H.L.[Hong-Lin],
Zhu, C.L.[Cheng-Lu],
Zhang, Y.L.[Yun-Long],
Sun, Y.X.[Yu-Xuan],
Shui, Z.Y.[Zhong-Yi],
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Task-Specific Fine-Tuning via Variational Information Bottleneck for
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CVPR23(7454-7463)
IEEE DOI
2309
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Launet, L.[Laëtitia],
Colomer, A.[Adrián],
Mosquera-Zamudio, A.[Andrés],
Moscardó, A.[Anaďs],
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A Self-Training Weakly-Supervised Framework for Pathologist-Like
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ICIP22(3401-3405)
IEEE DOI
2211
Training, Pathology, Image analysis, Annotations,
Biological system modeling, Data models, Skin, self-training,
whole slide images
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Alhammad, S.[Sarah],
Zhao, K.[Kun],
Jennings, A.[Anthony],
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Efficient DNN-Based Classification of Whole Slide Gram Stain Images
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DICTA21(01-08)
IEEE DOI
2201
Training, Deep learning, Pathology, Microorganisms, Protocols, Oils,
Microscopy, Bacteria Classification, DNN, Computer Aided Diagnosis,
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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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Chan, L.,
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Rowsell, C.,
Plataniotis, K.,
Damaskinos, S.,
HistoSegNet: Semantic Segmentation of Histological Tissue Type in
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ICCV19(10661-10670)
IEEE DOI
2004
biological tissues, convolutional neural nets,
image segmentation, medical image processing, random processes, Cams
BibRef
Stanisavljevic, M.[Milos],
Anghel, A.[Andreea],
Papandreou, N.[Nikolaos],
Andani, S.[Sonali],
Pati, P.[Pushpak],
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Springer DOI
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Gadermayr, M.[Michael],
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Domain Adaptive Classification for Compensating Variability in
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ICIAR16(616-622).
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1608
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Toutain, M.,
Lézoray, O.,
Audigié, F.,
Busoni, V.,
Rossi, G.,
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El Moataz, A.,
Analysis of Whole Slide Images of Equine Tendinopathy,
ICIAR12(II: 440-447).
Springer DOI
1206
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Chapter on Medical Applications, CAT, MRI, Ultrasound, Heart Models, Brain Models continues in
Fluorescence Analysis, Microscopic Analysis, Cells .