English(EN) CRISP -- Clustering-Based Redundancy-Reduced Instance Sampling for Pathology Case Representation and Retrieval

新的CRISP框架自动化病理WSI分析

作者 PulseAugur 编辑部 · [2 个来源] · 2026-05-22 22:06

研究人员开发了CRISP，一个用于分析数字病理学中多个全切片图像（WSIs）的无监督框架。该两阶段系统首先减少单个WSI内的冗余，然后使用聚类来选择整个病例的代表性图像块集。CRISP旨在捕捉病例级别的异质性并作为检索索引，通过利用目前在多WSI病例中被忽视的信息，有可能改善诊断和治疗计划。 AI

影响自动化分析多个病理切片，通过利用被忽视的数据，有可能提高诊断准确性和治疗计划。

排序理由该集群包含一篇详细介绍新方法的学术论文。

AI 生成摘要 · Google Gemini · 来自 2 个来源。我们如何撰写摘要 →

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arXiv cs.AI TIER_1 English(EN) · Zahra Rahimi Afzal, Wataru Uegami, Saghir Alfasly, Saba Yasir, Judy C. Boughey, Matthew P. Goetz, Krishna R. Kalari, H. R. Tizhoosh · 2026-05-26 04:00

CRISP -- 基于聚类的冗余减少实例采样，用于病理病例表示和检索

arXiv:2605.24253v1 Announce Type: cross Abstract: Digital pathology archives increasingly contain multiple whole-slide images (WSIs) per case, capturing spatially distinct tumour regions and reflecting intrinsic morphological heterogeneity. However, most existing approaches rely …
arXiv cs.IR (Information Retrieval) TIER_1 English(EN) · H. R. Tizhoosh · 2026-05-22 22:06

CRISP -- 基于聚类的冗余度降低实例采样，用于病理病例表示和检索

Digital pathology archives increasingly contain multiple whole-slide images (WSIs) per case, capturing spatially distinct tumour regions and reflecting intrinsic morphological heterogeneity. However, most existing approaches rely on a single pathologist-selected slide, thereby di…