Abstract
Accurately finding the region of interest is a very vital step for segmenting organs in medical image processing. We propose a novel approach of automatically identifying region of interest in Computed Tomography Image (CT) i... | Find, read and cite all the research you need on Tech Science Press
Highlights
Abdominal organ accurate segmentation is very vital in automatic disease diagnosis
3) We use a novel approach to track the growing region changes across the CT image sequence in detecting region of interest, given a seed point as our input
We used quantitative and qualitative analysis to measure the accuracy against the given ground truth and our results presented a better performance than other generic approaches for automatic region of interest detection of organs in abdominal CT images
Summary
Abdominal organ accurate segmentation is very vital in automatic disease diagnosis. As abdominal organs are closely packed together, separation of individual organs is a challenge in medical image processing as the accuracy for this task largely depends on the accuracy to identify the Region of Interest in CT images. A first step that is done during segmentation of a particular organ in an abdominal CT scan is identifying a region of interest. Having a poor located region of interest have got drastic impact on the accuracy of segmentation of a specific organ. Over the years there have been slow advancement on the method to automatically identify region of interest which have resulted in making automatic segmentation of an organ a difficult task to reach useable accuracy. This has resulted in many researchers opting to use human aided region of interest identification in which its prone to a lot of human errors. Once the Region of Interest is identified further analysis are applied on the region of interest to completely isolate the organ from the rest of the tissues around it
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