全幻灯片图像中乳腺癌转移的自动检测

Pallvi Grover, R. Singh
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引用次数: 1

摘要

癌症被认为是当今世界上传播最广泛的疾病之一。许多患有这种疾病的人不知道癌症的事实。女性更容易患乳腺癌。当健康细胞生长失控,形成大量细胞形成肿瘤时,癌症就会在体内扩散。本文描述了一种在全幻灯片图像中自动检测乳腺癌转移的算法。目前检测乳腺淋巴结转移的程序是手动且耗时的,在此过程中,专门检测和表征肿瘤区域的经验丰富的病理学家需要花费数小时来分析组织学切片。该算法利用先进的图像处理和机器学习的能力来提高检测精度以及在整个幻灯片图像中定位肿瘤区域所需的总体时间。
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Automated Detection of Breast Cancer Metastases in Whole Slide Images
Cancer is considered as one of the most widely spread disease in today’s world. Many people are suffering from this disease unaware of the facts about cancer. Women are more likely to suffer from breast cancer. Cancer spread in the body when the healthy cells grow out of control and form a mass of cells resulting in tumor. This paper describes an algorithm for automated detection of breast cancer metastases in Whole Slide Images. The current procedure for detecting metastases in a breast lymph node is manual and time-consuming in which an experienced pathologist specializing in detection and characterization of tumor regions spends hours to analyze histological slides. This algorithm leverages the capability of advanced Image Processing and Machine learning to improve the detection accuracy as well as overall time needed to localize tumorous regions in Whole Slide Image.
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