Fuzzy rule-based segmentation of CT brain images of hemorrhage for compression

This paper presents segmentation of hemorrhage from the computed tomography image. Fuzzy rule-based technique constituting three parameters namely mean difference, mode difference and grey level intensity is used. These parameters are fuzzified into four fuzzy regions with trapezoidal membership functions. The segmented arbitrary shaped region of interest information is employed in JPEG2000 encoder while encoding the image. It encodes ROI with highest priority in allocating bits as well as in transmission. 15 CT image slices with hemorrhage were used in the experiment. Experimental results shows good segmentation of hemorrhage region from CT images and allows encoding image at any desired bit rate, while maintaining lossless in ROI and lossy/lossless in non-ROI.

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