Open AccessImage Contrast Improvement in Image Fusion between CT and MRI images of Brain Cancer Patients
Author(s) -
Annisa Tenri Maya,
Suryono Suryono,
Choirul Anam
Publication year - 2021
Publication title -
international journal of scientific research in science and technology
Language(s) - English
Resource type - Journals
eISSN - 2395-602X
pISSN - 2395-6011
DOI - 10.32628/ijsrst218110
Subject(s) - image fusion , artificial intelligence , contrast (vision) , contrast to noise ratio , computer vision , image registration , computer science , magnetic resonance imaging , fusion , noise (video) , scanner , image noise , nuclear medicine , image (mathematics) , image quality , medicine , radiology , linguistics , philosophy
Medical image fusion has been carried out to obtain information benefits from multi-modalities of medical images. The purpose of this study is to improve the image contrast of fusion image with adaptive method. The median filter was implemented to the images before registration to remove noise for obtaining good image fusion. Geometric transformation-based image registration was used to automatically align two images of computed tomography (CT) scanner and magnetic resonance imaging (MRI) to a common coordinate system. After that, the image contrast was improved with adaptive method. Finally, the fused image was assessed using the signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR). From this study, it was found that the average SNR value in the image fusion before contrast improvement is 0.09 and after that is 0.73. While the average CNR value in image fusion before contrast improvement is 1.54 and after that is 1.79. It means that the CNR increases 14.02%.