Computed Tomography Medical Image Compression using Conjugate Gradient
Gottapu Sasibhushana Rao, S. Saradha Rani, Bhima Prabhakara Rao · 2019
Image compression which is a subset of data compression plays a crucial task in medical field. The medical images like CT, MRI, PET scan and X-Ray imagery which is a huge data, should be compressed to facilitate storage capacity without losing its details to diagnose the patient correctly. Now a days artificial neural network is being widely researched in the field of image processing. This paper examines the performance of a feed forward artificial neural network with learning algorithm as conjugate gradient. This work performs a comparison between Conjugate gradient technique and Gradient Descent algorithm is done. MSE and PSNR are used as quality metrics. The investigation is carried on CT scan of lower abdomen medical image.