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Mitosis Detection in Breast Cancer Using Superpixels and Ensemble Classifiers

机译:使用超像素和集合分类器的乳腺癌患者裂伤检测

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摘要

Determining the severity and potential aggressiveness of breast cancer is an important step in the determination of the treatment options for a patient. Mitosis activity is one of the main components in breast cancer severity grading. Currently, mitosis counting is a laborious, prone to processing errors, done manually by a pathologist. This paper presents a novel approach for automatic mitosis detection, where promising candidates are selected from a superpixel segmentation of the image and classified using an ensemble classifier created from a selection from a pool of different color spaces, different features vector.
机译:确定乳腺癌的严重程度和潜在的侵袭性是测定患者治疗方案的重要步骤。有丝分裂活动是乳腺癌严重程度分级的主要成分之一。目前,有丝分裂计数是一种艰苦的,容易处理误差,由病理学家手动完成。本文介绍了一种新的自动丝分裂检测方法,其中有希望的候选者选自图像的超像素分割,并使用从不同颜色空间池,不同的特征向量中选择的集合分类器进行分类。

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