乳腺癌和妇科癌症的计算病理学
Computational Pathology for Breast Cancer and Gynecologic Cancer.
作者信息
Wang Ching-Wei, Muzakky Hikam
机构信息
Graduate Institute of Biomedical Engineering, National Taiwan University of Science and Technology, Taipei 106335, Taiwan.
出版信息
Cancers (Basel). 2023 Feb 2;15(3):942. doi: 10.3390/cancers15030942.
Abstract
Advances in computation pathology have continued at an impressive pace in recent years [...].
摘要
近年来，计算病理学的进展一直以惊人的速度持续着[……]。
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本文引用的文献
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A Soft Label Deep Learning to Assist Breast Cancer Target Therapy and Thyroid Cancer Diagnosis.一种用于辅助乳腺癌靶向治疗和甲状腺癌诊断的软标签深度学习
Cancers (Basel). 2022 Oct 28;14(21):5312. doi: 10.3390/cancers14215312.
2
Deep learning-based image analysis predicts PD-L1 status from H&E-stained histopathology images in breast cancer.基于深度学习的图像分析可从乳腺癌的 H&E 染色组织病理学图像预测 PD-L1 状态。
Nat Commun. 2022 Nov 8;13(1):6753. doi: 10.1038/s41467-022-34275-9.
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Fast cross-staining alignment of gigapixel whole slide images with application to prostate cancer and breast cancer analysis.千兆像素全玻片图像的快速交叉染色对齐及其在前列腺癌和乳腺癌分析中的应用。
Sci Rep. 2022 Jul 8;12(1):11623. doi: 10.1038/s41598-022-15962-5.
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Multimodal data integration using machine learning improves risk stratification of high-grade serous ovarian cancer.基于机器学习的多模态数据整合提高了高级别浆液性卵巢癌的风险分层。
Nat Cancer. 2022 Jun;3(6):723-733. doi: 10.1038/s43018-022-00388-9. Epub 2022 Jun 28.
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Weakly supervised deep learning for prediction of treatment effectiveness on ovarian cancer from histopathology images.基于弱监督深度学习的卵巢癌病理图像治疗效果预测。
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Fast Segmentation of Metastatic Foci in H&E Whole-Slide Images for Breast Cancer Diagnosis.用于乳腺癌诊断的苏木精-伊红全切片图像中转移灶的快速分割
Diagnostics (Basel). 2022 Apr 14;12(4):990. doi: 10.3390/diagnostics12040990.
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