Vision transformer and explainable transfer learning models for auto detection of kidney cyst, stone and tumor from CT-radiography
BRAC University · Bangladesh University of Health Sciences · +4 more institutions
Abstract
Renal failure, a public health concern, and the scarcity of nephrologists around the globe have necessitated the development of an AI-based system to auto-diagnose kidney diseases. This research deals with the three major renal diseases categories: kidney stones, cysts, and tumors, and gathered and annotated a total of 12,446 CT whole abdomen and urogram images in order to construct an AI-based kidney diseases diagnostic system and contribute to the AI community's research scope e.g., modeling digital-twin of renal functions. The collected images were exposed to exploratory data analysis, which revealed that the images from all of the classes had the same type of mean color distribution. Furthermore, six…
Citation impact
- FWCI
- 20.26
- Percentile
- 100%
- References
- 34
Authors
6Topics & keywords
- Deep learning
- Artificial intelligence
- Computer science
- Transfer of learning
- Radiography
- Ray casting
- Medicine
- Radiology
- Good health and well-being