Artificial Intelligence in Radiology for X-Ray and CT-Scan Image Analysis
Dr. Amit Ray
Compassionate AI Lab, Radiology Division
With artificial intelligence it is possible to analyze and interpret large amounts of radiological images efficiently. Late detection of disease significantly increases treatment costs and reduces survival rates. Often visual human interpretation of an isolated image are time-consuming, difficult and expensive. Artificial intelligence in healthcare especially in radiology has tremendous scope. Recently, AI for radiology uses deep learning, reinforcement learning, and other machine learning algorithms to systematically assess x-ray, CT Scan and MRI images of and instantly provide detailed reports on their findings.
AI algorithms read medical images like a radiologist, they identify the hidden patterns in the image and relate them with medical data. The AI systems are trained using vast numbers of images like CT scans, magnetic resonance imaging (MRI), ultrasound or nuclear imaging. New AI tools that excel at medical image analysis can automatically detect complex anomalous patterns in radiological images and provide quantitative information on disease .
Studies have shown that computer aided screening can decrease false negatives by ~45% . The AI machines reading radiology studies correctly, reaching around 95 percent accuracy . The AI tools can rapidly review a number of images, prior images, patient history and other medical data, and then extract the most meaningful insights, which can then be verified by the radiologist.… Read more..