Digital Histopathology
- December 12, 2021
- Posted by: OptimizeIAS Team
- Category: DPN Topics
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Digital Histopathology
Subject – Science and Tech
Context – AI tool to simplify identification of cancerous tissue in tumours
Concept –
- Indian Institute of Technology Madras researchers use a combination of deep learning techniques and traditional machine learning to develop a tool that can diagnose cancer by looking at whole slide images of the tumour.
- The tool has been tested on datasets of breast, liver and colon cancer tissue images.
- It is economical in terms of the time required to process the images and analyse them.
- Traditionally, histopathologists slice the tumour tissue into approximately 20-micron-thick slices which they put on slides.
- They look at enlarged images of the slides and go over it cell by cell to manually classify it as cancerous or otherwise.
- This is highly time-consuming, and it is to alleviate this burden that digital histopathology developed.
- In this, after preparing the slides, the entire slide is scanned using a high-resolution microscope and digitised. This is then analysed using computerised tools.