Machine Learning and Deep Learning Techniques for MRI and CT Images

Shayan Nalbandian¹ Amirreza Rouhbakhshmeghrazi²

1) Department of Software, Northwestern Polytechnical University, Xi’An, Shaanxi, China,
2) Department of Electronic Information, Northwestern Polytechnical University, Xi’An, Shaanxi, China, Email:

Publication : 2nd International Congress on Science, engineering & New Technologies(secongress.com)
Abstract :
Machine learning has become a powerful tool in medical imaging. It can be used to improve the accuracy of diagnostic tests, personalize treatments, and make healthcare more efficient. Neural network-based techniques are a type of machine learning that is becoming increasingly popular because they can learn from large amounts of data and solve complex problems. Recent developments in machine learning and deep learning have led to improved performance in image processing and understanding, including medical image processing in radiation-based medical sciences. These techniques can now effectively handle a wide range of tasks and often outperform earlier, more superficial approaches. Current research aims to organize and understand the latest advancements in these fields to further enhance their capabilities and applications.
Keywords : Deep Learning Machine Learning Computed Tomography Image Processing Magnetic Resonance Imaging