Suppr超能文献

一种用于病理学中乳腺组织微阵列(TMA)采集与分类的计算机辅助诊断(CAD)系统。

A CAD System for the Acquisition and Classification of Breast TMA in Pathology.

作者信息

Fernández-Carrobles M Milagro, Bueno Gloria, Déniz Oscar, Salido Jesús, García-Rojo Marcial, González-López Lucía

机构信息

VISILAB, Universidad de Castilla-La Mancha, Spain.

Department of Pathology, Hospital de Jerez de la Frontera, Spain.

出版信息

Stud Health Technol Inform. 2015;210:756-60.

Abstract

Breast cancer is the most common type of cancer and the fifth leading cause of death in women over 40. Therefore, prompt diagnostic and treatment is essential. In this work a TMA Computer Aided Diagnosis (CAD) system has been implemented to provide support to pathologists in their daily work. For that purpose, the tool covers each and every process from the TMA core image acquisition to their individual classification. The first process includes: tissue core location, segmentation and rigid registration of digital microscopic images acquired at different magnifications (5x, 10x, 20x, 20x and 40x) from different devices. The classification process allows performing the core classification selecting different types of color models, texture descriptors and classifiers. Finally, the cores are classified into three categories: malignant, doubtful and benign.

摘要

乳腺癌是最常见的癌症类型,也是40岁以上女性的第五大死因。因此,及时诊断和治疗至关重要。在这项工作中,已实施了一种组织微阵列(TMA)计算机辅助诊断(CAD)系统,以在病理学家的日常工作中提供支持。为此,该工具涵盖了从TMA核心图像采集到其个体分类的每一个过程。第一个过程包括:组织核心定位、分割以及对从不同设备以不同放大倍数(5倍、10倍、20倍、20倍和40倍)获取的数字显微图像进行刚性配准。分类过程允许通过选择不同类型的颜色模型、纹理描述符和分类器来进行核心分类。最后,核心被分为三类:恶性、可疑和良性。

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验