Deep Learning-Based Object Detection Strategies for Disease Detection and Localization in Chest X-Ray Images
Yi-Ching Cheng, Yi-Chieh Hung, Guan-Hua Huang, Tai-Been Chen, Nan-Han Lu, Kuo-Ying Liu, Kuo-Hsuan Lin · 2024
Read Deep Learning-Based Object Detection Strategies for Disease Detection and Localization in Chest X-Ray Images by Yi-Ching Cheng, Yi-Chieh Hung, Guan-Hua Huang, Tai-Been Chen, Nan-Han Lu, Kuo-Ying Liu, Kuo-Hsuan Lin (2024) in the Tower of Babel, a free online library of public-domain works preserved in clean, searchable text. No sign-up. The full text is served as a plain-text file at a predictable URL, where text is present: https://antarctic-labs.com/tower-of-babel/pmc-11640298.txt.
Description
Cheng and co-authors present a 2024 study on teaching computers to find disease signs in chest X-ray images. Doctors read these images by eye, which is slow and can vary from reader to reader. A steady automated reader could flag sick spots and mark where they sit in the image.
The team trained its models on labeled images from one hospital in Taiwan. They test how the share of healthy images in training changes the results. They also test methods that learn from very few sick cases. Adding a simple sick-or-healthy sort step helped in all setups. Models of one common type beat a newer type across the tests, and the authors offer the setup as a more reliable aid for clinics.
Catalog record
| CREATOR | Yi-Ching Cheng, Yi-Chieh Hung, Guan-Hua Huang, Tai-Been Chen, Nan-Han Lu, Kuo-Ying Liu, Kuo-Hsuan Lin |
|---|---|
| YEAR | 2024 |
| COLLECTION | PAPERS |
| FORMAT | TXT |
| FILE SIZE | 43 KB |
| VERSION | 1.0 |
| LICENSE | CC BY 4.0 |
| RIGHTS | CC BY |
| SOURCE | Europe PMC |