Information maximization-based clustering of histopathology images using deep learning
Mahfujul Islam Rumman, Naoaki Ono, Kenoki Ohuchida, MD. Altaf-Ul-Amin, Ming Huang, Shigehiko Kanaya · 2023
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Description
Mahfujul Islam Rumman and co-authors cluster pancreas tissue images without any labels in a 2023 study. Pancreatic cancer hides deep and tangles with vessels, so microscope diagnosis carries heavy weight. Mouse tumors that mimic the human disease supplied whole-slide images.
Random patches from the slides were squeezed by an autoencoder into a compact code space. An information-maximizing method then grouped look-alike patches with no annotation at all. The clusters separate tissue patterns that pathologists care about. Unsupervised sorting could pre-screen slides and flag the odd ones for expert eyes, the authors suggest.
Catalog record
| CREATOR | Mahfujul Islam Rumman, Naoaki Ono, Kenoki Ohuchida, MD. Altaf-Ul-Amin, Ming Huang, Shigehiko Kanaya |
|---|---|
| YEAR | 2023 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 45 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |