Applications of Curvelet Transform: A Review

Abstract

The use and examination of 3D picture files of the human body, generally gathered from a Computed Tomography (CT) or Magnetic Resonance Imaging (MRI) scanner, to diagnose diseases, guide medical operations such as surgery planning, or for research purposes, is known as medical image processing. It allows for a comprehensive study of the internal anatomy while being non-invasive. 3D models of anatomical structures of interest can be built and studied in order to improve patient treatment outcomes, develop better medical equipment and drug delivery systems, and arrive at more accurate diagnoses. It has recently become one of the most essential instruments for medical improvement. It was shown that curvelet transformations performed better than other transforms on medical data. In tests, Curvelet greatly improves the classification of aberrant tissues in scans and reduces the surrounding noise. We gave an overview of contemporary advances and technologies including curvelet transform as well as digital subtraction angiography in this paper. The study also discusses the uses of wavelet and ridglet transforms, as well as the drawbacks that inspired the use of the curvelet transform for improved image visualisation.