We present an electronic colon cleansing algorithm using a new segmentation technique based on segmentation rays. These rays are specially designed to analyze the intensity profile as they traverse through the dataset...
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ISBN:
(纸本)0819444286
We present an electronic colon cleansing algorithm using a new segmentation technique based on segmentation rays. These rays are specially designed to analyze the intensity profile as they traverse through the dataset. When this intensity profile matches any of the pre-defined profiles, the rays perform certain task of reconstruction. We use these rays to detect the intersection between air and residual fluid, and between residual fluid and soft-tissue. One of the most important advantages of segmentation rays over other segmentation techniques is the detection of partial volume regions. segmentation rays can accurately detect partial volume regions and remove them if needed. Once partial volume is eliminated, removal of other unwanted regions (e.g., tagged fluid) is relatively easy. This approach to electronic cleansing is extremely fast as it requires minimal computation.
We propose a novel approach for segmentation and digital cleansing of endoscopic organs. Our method can be used for a variety of segmentation needs with little or no modification. It aims at fulfilling the dual and of...
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ISBN:
(纸本)0780364783
We propose a novel approach for segmentation and digital cleansing of endoscopic organs. Our method can be used for a variety of segmentation needs with little or no modification. It aims at fulfilling the dual and often conflicting requirements of a fast and accurate segmentation and also eliminates the undesirable partial volume effect which contemporary approaches cannot. For segmentation and digital cleansing, we use the peculiar characteristics exhibited by the intersection of any two distinct-intensity regions. To detect these intersections we cast rays through the volume, which we call the segmentation rays as they assist in the segmentation. We then associate a certain task of reconstruction and classification with each intersection the ray detects. We further use volumetric contrast enhancement to reconstruct surface lost by segmentation (if any), which aids in improving the quality of the volume rendering.
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