Abstract
Over the past century, scientific advances in diagnostic devices have offered new potential for noninvasive diagnoses and entrenched computed tomography as a critical component of today's health services. The multidisciplinary field of health image analysis is one of the key areas of innovation that represents these achievements. This area of rapid growth deals with a wide range of operations that support the whole data flow in current health monitoring systems (from raw data capture through digital image transfer). These technologies now have better spatial and luminance resolutions, as well as quicker collection periods, resulting in a large volume of high critical image files that must be appropriately processed and evaluated in order to provide reliable diagnostics findings. This article examines the core kinds of clinical image analysis, as well as the background of various imaging technologies and the major difficulties and developments in the field.
Highlights
The method and practice of imaging the inside of a body for diagnostic assessment and therapeutic procedures, and a visual depiction of the functionality of specific organs and systems, is known as medical imaging
LITERATURE REVIEW Medical image processing, according to [3], includes the utilization and investigation of three - dimensional sets of data of the body acquired most frequently from the a Magnetic Resonance Imaging (MRI) or Computed Tomography (CT) scanner to make a diagnosis for pathologies, instruct invasive procedures such as preoperative treatment, or for investigation
Radiographers, technologists, and doctors use medical computer vision to better comprehend the physiology of patients or patient populations
Summary
The method and practice of imaging the inside of a body for diagnostic assessment and therapeutic procedures, and a visual depiction of the functionality of specific organs and systems, is known as medical imaging (physiological). Medical imaging is often thought to refer to a collection of non-invasive procedures for producing pictures of the body's interior structures. In this limited sense, sonography may be thought of as the solution of inverse mathematics problems. The multidisciplinary field of medical image processing is one of the key areas of innovation that exemplifies these breakthroughs This area of fast growth deals with a wide range of operations that support the whole data flow in current medical imaging systems (from raw data capture through digital picture transfer).
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