Reducing annotation effort in digital pathology: A Co-Representation learning framework for classification tasks
出版年份 2020 全文链接
标题
Reducing annotation effort in digital pathology: A Co-Representation learning framework for classification tasks
作者
关键词
Digital pathology, Co-representation learning, Deep metric learning, Informative triplet sampling, Soft-multi-pair loss, Limited annotations, Nuclei classification, Mitosis detection, Tissue type classification
出版物
MEDICAL IMAGE ANALYSIS
Volume 67, Issue -, Pages 101859
出版商
Elsevier BV
发表日期
2020-10-09
DOI
10.1016/j.media.2020.101859
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- Predicting survival from colorectal cancer histology slides using deep learning: A retrospective multicenter study
- (2019) Jakob Nikolas Kather et al. PLOS MEDICINE
- Whole slide imaging equivalency and efficiency study: experience at a large academic center
- (2019) Matthew G. Hanna et al. MODERN PATHOLOGY
- Weakly supervised mitosis detection in breast histopathology images using concentric loss
- (2019) Chao Li et al. MEDICAL IMAGE ANALYSIS
- BACH: Grand challenge on breast cancer histology images
- (2019) Guilherme Aresta et al. MEDICAL IMAGE ANALYSIS
- Generative adversarial network in medical imaging: A review
- (2019) Xin Yi et al. MEDICAL IMAGE ANALYSIS
- Hover-Net: Simultaneous segmentation and classification of nuclei in multi-tissue histology images
- (2019) Simon Graham et al. MEDICAL IMAGE ANALYSIS
- Neural Image Compression for Gigapixel Histopathology Image Analysis
- (2019) David Tellez et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- DeepMitosis: Mitosis detection via deep detection, verification and segmentation networks
- (2018) Chao Li et al. MEDICAL IMAGE ANALYSIS
- A Cluster-then-label Semi-supervised Learning Approach for Pathology Image Classification
- (2018) Mohammad Peikari et al. Scientific Reports
- Deep learning based tissue analysis predicts outcome in colorectal cancer
- (2018) Dmitrii Bychkov et al. Scientific Reports
- A survey on deep learning in medical image analysis
- (2017) Geert Litjens et al. MEDICAL IMAGE ANALYSIS
- Locality Sensitive Deep Learning for Detection and Classification of Nuclei in Routine Colon Cancer Histology Images
- (2016) Korsuk Sirinukunwattana et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- Diagnostic Concordance Among Pathologists Interpreting Breast Biopsy Specimens
- (2015) Joann G. Elmore et al. JAMA-JOURNAL OF THE AMERICAN MEDICAL ASSOCIATION
- Assessment of algorithms for mitosis detection in breast cancer histopathology images
- (2015) Mitko Veta et al. MEDICAL IMAGE ANALYSIS
- Virtual microscopy and digital pathology in training and education
- (2012) Peter W. Hamilton et al. APMIS
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