Image processing has become a vital piece of technology in contemporary medicine, transforming many facets of medical study, diagnosis, and treatment. An extensive analysis of image processing methods and their uses in the medical field is presented in this work. This paper emphasizes the basic value of medical imaging in illness diagnosis and therapy planning. It explores the different image processing methods used to improve and examine medical images. The techniques mentioned consist of image segmentation, registration, classification, and enhancement. Through the use of techniques including noise reduction, contrast enhancement, and spatial resolution improvement, image enhancement methods seek to improve the visual quality of medical pictures. For noise reduction, several filtering algorithms are frequently used, including wavelet transforms and median filtering. Adaptive filtering and histogram equalization are two contrast enhancement techniques that are used to make structures in the images more apparent. A variety of image processing applications in healthcare are presented in the study. Medical research, image-guided surgery, image-based treatment planning, virtual reality visualization, and computer-aided diagnostics are some of these uses. Accurate illness identification, characterisation, and quantification are made possible by image processing techniques, which promote early diagnosis and individualized treatment plans. A literature on robotic surgeries, their interventions in health care, advantages and disadvantages of these methods is also shown.

Image Processing, Medical Imaging, Computer aided Diagnosis, Healthcare etc.,