Enhancing the efficiency in interpretation of medical imaging through state-of-the-art algorithms.
Artonical — Bringing AI To Medical Imaging
Category: Web Application | Machine Learning
Technology: 
Image processing has proven effective in various disciplines and medical field is certainly no exception. Chest X-Rays have been instrumental in diagnosing thoracic diseases. Yet, radiology is a complex discipline with the potential for human error in interpretation. Decision-making in radiology occurs under uncertain conditions, making infallible interpretations challenging.
Currently, the project is undergoing an extension (with a different name) utilizing the CheXpert dataset. The second phase is to create a consolidated dataset with the purpose to enhance the robustness of the algorithm, contributing to more accurate and reliable diagnostic outcomes. The current extension of this project is implemented using Spring 3.0 and Angular 17, The primary objective of this project is to provide an essential support to radiologist, aiding in accurate and efficient diagnosis. It serves as the 'second opinion', complementing the expertise of radiologist.
For further details on the project, you can look over this article Bringing AI To Medical Imaging.
Algorithm Workflow
- Validate and resize the image height/width to 224px.
- Preprocess the image i.e., perform feature extraction.
- Once, the algorithm extracted the features it passed the input vector values to the trained model; then model efficiently provides confidence scores (in %) with respect to each label.
