Abstract
In this investigation, automatic image segmentation is carried out on magnetic resonance image (MRI). A novel technique based on the maximum minimum measure is devised. The measure is improved by combining the smoothing and counting processes, and then normalising the number of maximum and minimum positions over the region of interest (ROI). Two parameters (MM_H and MM_V) are generated and used for the segmentation. The technique is tested on some brain MRIs of a human male from the Visible Human Project of the National Library of Medicine, National Institutes of Health, USA. Preliminary results indicate that the maximum minimum measure can provide effective parameters for human tissue characterization and image segmentation with an added advantage of faster in computation.
Original language | English |
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Pages (from-to) | 931-939 |
Journal | Proceedings of SPIE - The International Society for Optical Engineering |
Volume | 2710 |
DOIs | |
Publication status | Published - 1996 |
Event | Medical Imaging 1996 Image Processing - Newport Beach, CA, United States Duration: 12 Feb 1996 → 15 Feb 1996 |
Research Keywords
- Feature extraction
- Image segmentation
- Magnetic resonance image
- Maximum minimum measure