Chest X-Rays (CXRs) are widely used for diagnosing abnormalities in the heart and lung area. Automatically detecting these abnormalities with high accuracy could greatly enhance real world diagnosis processes Chest abnormality detection solution is built with an objective to develop a decision support system for data scientists and clinician to detect abnormalities in chest x-ray.
The solution is a computer vision prototype for the detection and identification of different types of anomalies from X-ray images, aimed at both data scientists and clinicians.
The solution enables timely clinical intervention support, cost optimization and improved quality of patient care. Chest abnormality detector enables quicker diagnosis and cheaper with a reduced reliance on the intervention of human experts.