Multi-Pass Adaptive Voting for Nuclei Detection in Histopathological Images.
Multi-Pass Adaptive Voting for Nuclei Detection in Histopathological Images.
复制标题
用于组织病理学图像中细胞核检测的多通道自适应投票
DOI：
10.1038/srep33985
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发表时间：
2016-10-03
影响因子：
4.6
通讯作者：
Madabhushi A
中科院分区：
文献类型：
--
作者：
Lu C;Xu H;Xu J;Gilmore H;Mandal M;Madabhushi A
在数字病理图像的背景下，细胞核检测通常是计算机辅助诊断和预后方案开发中关键的初始步骤。在过去几年中，虽然已经提出了许多细胞核检测方法，但这些方法中的大多数都对组织的染色质量做出了理想化的假设。在本文中，我们提出了一种新的多通道自适应投票（MPAV）细胞核检测方法，该方法专门针对因组织制备伪影而染色质量差且有噪声的图像。MPAV利用细胞核边界的对称性，并从边缘片段中自适应地选择梯度，以便对潜在的细胞核位置进行投票。MPAV在采用不同染色方法的三个队列中进行了评估：苏木精 - 伊红染色、CD31与苏木精染色以及Ki - 67染色，其中大多数细胞核染色不均匀且不精确。在总共47张图像以及近17700个手动标记的作为真实情况的细胞核中，MPAV能够实现卓越的性能，其精确率 - 召回率曲线下面积（AUC）达到0.73。此外，MPAV还优于三种最先进的细胞核检测方法，即单通道投票方法、多通道投票方法以及一种基于深度学习的方法。
Nuclei detection is often a critical initial step in the development of computer aided diagnosis and prognosis schemes in the context of digital pathology images. While over the last few years, a number of nuclei detection methods have been proposed, most of these approaches make idealistic assumptions about the staining quality of the tissue. In this paper, we present a new Multi-Pass Adaptive Voting (MPAV) for nuclei detection which is specifically geared towards images with poor quality staining and noise on account of tissue preparation artifacts. The MPAV utilizes the symmetric property of nuclear boundary and adaptively selects gradient from edge fragments to perform voting for a potential nucleus location. The MPAV was evaluated in three cohorts with different staining methods: Hematoxylin & Eosin, CD31 & Hematoxylin, and Ki-67 and where most of the nuclei were unevenly and imprecisely stained. Across a total of 47 images and nearly 17,700 manually labeled nuclei serving as the ground truth, MPAV was able to achieve a superior performance, with an area under the precision-recall curve (AUC) of 0.73. Additionally, MPAV also outperformed three state-of-the-art nuclei detection methods, a single pass voting method, a multi-pass voting method, and a deep learning based method.
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影响因子：
10.6
作者：
Ginsburg, Shoshana B.;Lee, George;Madabhushi, Anant
通讯作者：
Madabhushi, Anant
影响因子：
3.7
作者：
Basavanhally, Ajay;Viswanath, Satish;Madabhushi, Anant
通讯作者：
Madabhushi, Anant
影响因子：
4.6
作者：
Fatakdawala, Hussain;Xu, Jun;Madabhushi, Anant
通讯作者：
Madabhushi, Anant
DOI：
10.1109/tpami.1986.4767851
发表时间：
1986-11-01
影响因子：
23.6
作者：
CANNY, J
通讯作者：
CANNY, J
DOI：
10.1109/titb.2012.2199595
发表时间：
2013-03-01
影响因子：
7.7
作者：
Lu, Cheng;Mahmood, Muhammad;Mandal, Mrinal
通讯作者：
Mandal, Mrinal