Content-Based Image Retrieval and Image Classification System for Early Prediction of Bladder Cancer
Muhammed Yildirim, Ayman El-Baz, Jasjit S Suri · 2024
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Description
Early detection of bladder cancer is the goal of a 2024 study of image-based computer systems. Bladder cancer starts in the lining of the bladder and can spread if caught late. The study built two tools to support doctors as they judge a case. One tool classifies medical images. The other retrieves stored images that look most like a new one.
The retrieval system was tested in many forms. Five neural networks were tried for pulling features from images, along with two texture-based methods and seven ways to score how alike two images are. A network called DenseNet201 gave the best features. A cosine score, which compares the angle between feature lists, worked best for matching. The authors report the pairing gave the highest success in their tests.
Catalog record
| CREATOR | Muhammed Yildirim, Ayman El-Baz, Jasjit S Suri |
|---|---|
| YEAR | 2024 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 32 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |