Analysis and Validation of Image Search Engines in Histopathology.

IF 17.2 1区 工程技术 Q1 ENGINEERING, BIOMEDICAL
Isaiah Lahr, Saghir Alfasly, Peyman Nejat, Jibran Khan, Luke Kottom, Vaishnavi Kumbhar, Areej Alsaafin, Abubakr Shafique, Sobhan Hemati, Ghazal Alabtah, Nneka Comfere, Dennis Murphree, Aaron Mangold, Saba Yasir, Chady Meroueh, Lisa Boardman, Vijay H Shah, Joaquin J Garcia, H R Tizhoosh
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引用次数: 0

Abstract

Searching for similar images in archives of histology and histopathology images is a crucial task that may aid in patient tissue comparison for various purposes, ranging from triaging and diagnosis to prognosis and prediction. Whole slide images (WSIs) are highly detailed digital representations of tissue specimens mounted on glass slides. Matching WSI to WSI can serve as the critical method for patient tissue comparison. In this paper, we report extensive analysis and validation of four search methods bag of visual words (BoVW), Yottixel, SISH, RetCCL, and some of their potential variants. We analyze their algorithms and structures and assess their performance. For this evaluation, we utilized four internal datasets (1269 patients) and three public datasets (1207 patients), totaling more than 200, 000 patches from 38 different classes/subtypes across five primary sites. Certain search engines, for example, BoVW, exhibit notable efficiency and speed but suffer from low accuracy. Conversely, search engines like Yottixel demonstrate efficiency and speed, providing moderately accurate results. Recent proposals, including SISH, display inefficiency and yield inconsistent outcomes, while alternatives like RetCCL prove inadequate in both accuracy and efficiency. Further research is imperative to address the dual aspects of accuracy and minimal storage requirements in histopathological image search.

组织病理学图像搜索引擎的分析与验证。
在组织学和组织病理学图像档案中搜索相似图像是一项重要任务,可帮助进行病人组织对比,以实现从分流和诊断到预后和预测等各种目的。整张载玻片图像(WSI)是安装在玻璃载玻片上的组织标本的高度详细数字图像。将 WSI 与 WSI 匹配可作为患者组织比对的关键方法。在本文中,我们报告了对四种搜索方法视觉词袋(BoVW)、Yottixel、SISH、RetCCL 及其一些潜在变体的广泛分析和验证。我们分析了它们的算法和结构,并评估了它们的性能。在评估过程中,我们使用了四个内部数据集(1269 名患者)和三个公共数据集(1207 名患者),共计来自五个主要网站的 38 个不同类别/子类型的 20 多万个补丁。某些搜索引擎,如 BoVW,效率高、速度快,但准确率低。相反,像 Yottixel 这样的搜索引擎则表现出效率和速度,并能提供中等准确度的结果。包括 SISH 在内的最新提案显示出效率低下和结果不一致的问题,而 RetCCL 等替代方案则被证明在准确性和效率方面都存在不足。要解决组织病理学图像搜索的准确性和最低存储要求这两个方面的问题,进一步的研究势在必行。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
IEEE Reviews in Biomedical Engineering
IEEE Reviews in Biomedical Engineering Engineering-Biomedical Engineering
CiteScore
31.70
自引率
0.60%
发文量
93
期刊介绍: IEEE Reviews in Biomedical Engineering (RBME) serves as a platform to review the state-of-the-art and trends in the interdisciplinary field of biomedical engineering, which encompasses engineering, life sciences, and medicine. The journal aims to consolidate research and reviews for members of all IEEE societies interested in biomedical engineering. Recognizing the demand for comprehensive reviews among authors of various IEEE journals, RBME addresses this need by receiving, reviewing, and publishing scholarly works under one umbrella. It covers a broad spectrum, from historical to modern developments in biomedical engineering and the integration of technologies from various IEEE societies into the life sciences and medicine.
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