A Review on Transfer Learning and Generative Adversarial Networks for Classification of ALL
Ketan Mepani, Nikunj H. Domadiya · 2022 6th International Conference on Electronics, Communication and Aerospace Technology · 2022
Leukemia is classified as either myelogenous (also called myeloid) or lymphocytic depending on which types of white blood cells are affected. Most current AI techniques for medical image analysis rely on supervised learning, which contains a substantial amount of labelled data. Medical images annotations are typically pricey and not readily available in large quantities for this limitation GAN model require to generate images in medical field. There are Deep learning has many vital applications, including medical image processing, which is anticipated to significantly reduce the burden of doctors. The ability of Generative Adversarial Networks is to produce high-quality visual samples from the images in less time. This research examines the state of Acute Lymphoblastic Leukemia (ALL) prediction approach with Generative Adversarial Network (GAN) research in the field of medical imaging and examines various transfer learning models. This research also discussions upcoming research Leukemia and problems of GAN for medical image analysis.