Novel lymph node segmentation and proliferation index measurement for skin melanoma biopsy images
Novel lymph node segmentation and proliferation index measurement for skin melanoma biopsy images
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DOI：
10.1016/j.compmedimag.2019.01.006
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发表时间：
2019-04-01
影响因子：
5.7
通讯作者：
Mandal, Mrinal
中科院分区：
文献类型：
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作者：
Alheejawi, Salah;Xu, Hongming;Mandal, Mrinal
淋巴系统是人体的免疫系统，包括遍布全身的血管网络、淋巴结和淋巴液。淋巴结被认为是从淋巴管中收集淋巴液的净化单位。由于淋巴结收集了从恶性肿瘤中逃逸出来并试图扩散到身体其他部位的癌细胞，因此淋巴结分析对许多类型的皮肤癌和乳腺癌的分期都很重要。在本文中，我们提出了一种计算机辅助诊断（CAD）方法，该方法在活检图像中分割淋巴结和黑色素瘤区域并测量增殖指数。该方法分为两个阶段。首先，采用一种基于直方图和高频特征的自动化技术对活检图像中的淋巴结进行分割。在第二阶段，通过比较活跃核和被动核的数量来计算黑色素瘤区域的增殖指数。对76张不同淋巴结图像的实验结果表明，所提出的分割技术可以鲁棒地分割淋巴结，准确率在90%以上。所提出的扩散指数计算复杂度低，平均错误率小于1.5%。(C) 2019 Elsevier Ltd.版权所有。
The lymphatic system is the immune system of the human body, and includes networks of vessels spread over the body, lymph nodes, and lymph fluid. The lymph nodes are considered as purification units that collect the lymph fluid from the lymph vessels. Since the lymph nodes collect the cancer cells that escape from a malignant tumor and try to spread to the rest of the body, the lymph node analysis is important for staging many types skin and breast cancers. In this paper, we propose a Computer Aided Diagnosis (CAD) method that segments the lymph nodes and melanoma regions in a biopsy image and measure the proliferation index. The proposed method contains two stages. First, an automated technique is used to segment the lymph nodes in a biopsy image based on histogram and high frequency features. In the second stage, the proliferation index for the melanoma regions is calculated by comparing the number of active and passive nuclei. Experimental results on 76 different lymph node images show that the proposed segmentation technique can robustly segment the lymph nodes with more than 90% accuracy. The proposed proliferation index calculation has low complexity and has an average error rate of less than 1.5%. (C) 2019 Elsevier Ltd. All rights reserved.