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Liver and Tumor Segmentation in CT Images
Details
A new proposed method of fully automatic processing frameworks is given based on Geodesic Graph-cut Active Contour algorithms. The algorithm is applied to image segmentation using two different kinds of local neighborhoods in constructing the graph. The major problem with Graph-Cut approach is the incorrect selection of Liver Region with coloring similar to user's scribbles being identified as a tumor region. Results can be improved by using the proposed new technique based on Geodesic Graph-Cut method. This system has concentrated on finding a fast and interactive segmentation method for liver and tumor segmentation. In the preprocessing stage, the CT image process is carried over with mean shift filter and statistical thresholding method for reducing processing area with improving detection rate. Second stage is Liver Segmentation; the liver region has been segmented using the algorithm of the proposed method. In the next stage, Tumor segmentation also followed the same steps. Finally the liver and tumor regions are separately segmented from the computer tomography image.
Autorentext
Christo Ananth, Researcher is a member of 133 Professional Bodies over the globe.He is serving as Editorial board member/Reviewer of 410 SCI/ISI/Scopus/Web of Science indexed International Journals and 151 Refereed and Indexed International Journals. He is chosen as an elected fellow from ISECE (Malaysia) and a Life Member from ISTE (India)
Weitere Informationen
- Allgemeine Informationen
- GTIN 09786202053358
- Genre Electrical Engineering
- Sprache Englisch
- Anzahl Seiten 64
- Herausgeber LAP LAMBERT Academic Publishing
- Größe H220mm x B150mm x T4mm
- Jahr 2017
- EAN 9786202053358
- Format Kartonierter Einband (Kt)
- ISBN 6202053356
- Veröffentlichung 21.09.2017
- Titel Liver and Tumor Segmentation in CT Images
- Autor Christo Ananth
- Gewicht 113g