Medical Imaging in Artificial Intelligence: a Literature Survey

EasyChair Preprint 9780

Abstract

The increase of human population and the number of diseases each day causes the need for a fast and accurate diagnosis. In recent years, artificial intelligence (AI) technologies have greatly advanced and become a reality in many areas of our daily lives. In the health care field, numerous efforts are being made to implement the AI technology for practical medical treatments. With the rapid developments in machine learning algorithms and improvements in hardware performances, the AI technology is expected to play an important role. Artificial intelligence in medical diagnosis helps with medical decision making, management, automation, admin, and workflows. It can be used to diagnose cancer, triage critical findings in medical imaging, flag acute abnormalities, provide radiologists with help in prioritizing life threatening cases and help with the management of chronic diseases. Autonomous diagnosis is one of the popular research areas, which reduces the workload of the health workers and gives them the opportunity to spend more time on taking care of their patients while using the help of these systems for a fast and accurate diagnosis. But no matter if the diagnosis is done manually or by an autonomous system, image enhancement is very important since it directly affects the result of the diagnosis in both cases. This chapter includes recent studies which are related to image enhancement in healthcare applications.

Keyphrases: Adaptive Histogram Equalization, Artificial Intelligence, CLAHE, CT, MRI, Medical Imaging, deep learning, health care, image processing, medical image

@booklet{EasyChair:9780,
  author    = {Jayprakash Upadhyay and Ayushi Jaiswal},
  title     = {Medical Imaging in Artificial Intelligence: a Literature Survey},
  howpublished = {EasyChair Preprint 9780},
  year      = {EasyChair, 2023}}