基于深度学习的胃癌免疫组化图像淋巴细胞自动检测

2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS) Pub Date : 2017-06-22 DOI:10.1109/CBMS.2017.94

Emilio Garcia, Renato Hermoza, C. B. Castañón, Luis Cano, Miluska Castillo, Carlos Castanneda

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引用次数: 53

摘要

肿瘤浸润淋巴细胞(tumor -浸润淋巴细胞，til)近年来受到广泛关注，因为有证据表明它们与癌症预后有关。这些和其他类型的免疫细胞的分布和定位是病理学家特别感兴趣的，经常涉及免疫组织化学(IHC)图像的人工检查。提出了一种基于深度卷积神经网络的胃癌免疫组化图像淋巴细胞自动检测模型。作为这项工作的一部分创建的数据集是公开的，供未来的研究使用。

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Automatic Lymphocyte Detection on Gastric Cancer IHC Images Using Deep Learning

Tumor-infiltrating lymphocytes (TILs) have received considerable attention in recent years, as evidence suggests they are related to cancer prognosis. Distribution and localization of these and other types of immune cells are of special interest for pathologists, and frequently involve manual examination on Immunohistochemistry (IHC) Images. We present a model based on Deep Convolutional Neural Networks for Automatic lymphocyte detection on IHC images of gastric cancer. The dataset created as part of this work is publicly available for future research.

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2017 IEEE 30th International Symposium on Computer-Based Medical Systems (CBMS)

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