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Abstract

Medical imaging is a broad field of research and artificial intelligence used to explore such images is termed as AI-Imaging. AI-imaging is further divided into sub-branches including the computational, theoretical and practical experiments in wet and dry labs. The current research focuses on the background of medical imaging, recent advances in the field of medical imaging for oncology, challenges and possible solutions. During this research, some computational and programing tools are outlined. The process of image segmentation is important as it can help to explore the medical images in more detail. During this research, the steps involved in image segmentation are outlined and the numerical experiments are performed on a set of breast cancer medical images. It is concluded during this research that the achievements in this domain are always credited by the smart programing & computational tools and computer vision. The current research also outlines the step-wise protocols of deep learning, designed for different types of medical imaging such as X-rays, CT-scan and MRI are documented to provide a comprehensive understanding, that can help in bridging the two domains of medicine and computer vision, in a reliable and fruitful manner.

Keywords

Deep learning medical diagnostics medical imaging smart optimization tools

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Medical imaging and nano-engineering advances with artificial intelligence

Abstract

Keywords

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