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Breast fibroadenoma automatic detection using k-means based hybrid segmentation method

机译:乳腺纤维腺瘤自动检测采用基于K型混合分割方法

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摘要

Fibroadenoma is a benign tumor that has some features similar to a malignant one. The aim of this study was to examine the impact of fibroadenoma cases on the results of the automatic breast cancer diagnostic system based on the quantitative morphometric analysis of fine needle biopsy microscopic images. The database of 50 patients (500 images) of benign and malignant lesions used previously in our research was enriched by an additional 25 patients (250 images) of fibroadenoma cases. Experiments were performed using the k-means based hybrid segmentation method. The system was tested on a set of real case medical images with promising results.
机译:Fibroadenoma是一种良性肿瘤,具有与恶性人相似的一些特征。本研究的目的是研究纤维造型瘤病例对自动乳腺癌诊断系统结果的影响,基于细针活检微观图像的定量形态学分析。先前在我们的研究中使用的良性和恶性病变的50名患者(500张患者)的数据库由另外25名患者(250张图像)的纤维造型瘤病例进行富集。使用基于K-Means的混合分割方法进行实验。该系统在一组真实案例的医学图像上进行了测试,具有有希望的结果。

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