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一种用于获取高光谱和 RGB 组织病理学成像数据库的显微镜设置和方法。

A Microscope Setup and Methodology for Capturing Hyperspectral and RGB Histopathological Imaging Databases.

机构信息

Research Center on Software Technologies and Multimedia Systems, Universidad Politécnica de Madrid, 28031 Madrid, Spain.

Pathology and Neurooncology Unit, Instituto de Investigación Biomédicas I+12, Hospital Universitario 12 de Octubre, 28041 Madrid, Spain.

出版信息

Sensors (Basel). 2024 Aug 30;24(17):5654. doi: 10.3390/s24175654.

Abstract

The digitization of pathology departments in hospitals around the world is now a reality. The current commercial solutions applied to digitize histopathological samples consist of a robotic microscope with an RGB-type camera attached to it. This technology is very limited in terms of information captured, as it only works with three spectral bands of the visible electromagnetic spectrum. Therefore, we present an automated system that combines RGB and hyperspectral technology. Throughout this work, the hardware of the system and its components are described along with the developed software and a working methodology to ensure the correct capture of histopathological samples. The software is integrated by the controller of the microscope, which features an autofocus functionality, whole slide scanning with a stitching algorithm, and hyperspectral scanning functionality. As a reference, the time to capture and process a complete sample with 20 regions of high biological interest using the proposed method is estimated at a maximum of 79 min, reducing the time required by a manual operator by at least three times. Both hardware and software can be easily adapted to other systems that might benefit from the advantages of hyperspectral technology.

摘要

目前,全球医院的病理科已经实现了数字化。当前应用于病理样本数字化的商业解决方案包括一个带有 RGB 型相机的机器人显微镜。从捕获的信息量来看,这种技术非常有限,因为它只适用于可见电磁光谱的三个光谱带。因此,我们提出了一种结合 RGB 和高光谱技术的自动化系统。在整个工作过程中,描述了系统的硬件及其组件,以及开发的软件和工作方法,以确保正确捕获病理样本。该软件由显微镜的控制器集成,具有自动对焦功能、具有拼接算法的全玻片扫描功能以及高光谱扫描功能。作为参考,使用提出的方法对具有 20 个高生物学意义区域的完整样本进行采集和处理的估计时间最长为 79 分钟,这将手动操作人员所需的时间至少减少了三倍。硬件和软件都可以轻松适应可能受益于高光谱技术优势的其他系统。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/38a1/11398057/7d35e53896d6/sensors-24-05654-g007.jpg

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