A soft-segmentation visualization scheme for magnetic resonance images.
Prevalent visualization tools exploit gray value distribution in images through modified histogram equalization and matching technique, referred to as the window width/window level-based method, to improve visibility and enhance diagnostic value. The window width/window level tool is extensively used in magnetic resonance (MR) images to highlight tissue boundaries during image interpretation. However, the identification of different regions and distinct boundaries between them based on gray-level distribution and displayed intensity levels is extremely difficult because of the large dynamic range of tissue intensities inherent in MR images. We propose a soft-segmentation visualization scheme to generate pixel partitions from the histogram of MR image data using a connectionist approach and then generate selective visual depictions of pixel partitions using pseudo color based on an appropriate fuzzy membership function. By applying the display scheme in clinical examples in this study, we could demonstrate additional overlapping regions between distinct tissue types in healthy and diseased areas (in the brain) that could help improve the tissue characterization ability of MR images.
Mehta
Shashi Bhushan
SB
Institute of Nuclear Medicine and Allied Sciences, Timar pur, Delhi 110054, India. sbmehta@vsnl.com
Chaudhury
Santanu
S
Bhattacharyya
Asok
A
Jena
Amarnath
A
D000465:Algorithms; D001932:Brain Neoplasms / Q000175:diagnosis; D017143:Fuzzy Logic; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging