Segmentation of CT Images to Extract Liver using Algorithms
R V Manjunath1, K. Karibasappa2
1R V Manjunath Be*, Mtech, Assistant Professor, Department of Electronics & Communication Engineering, DSATM, Bangalore
2Dr. Karibasappa Kwadiki, Professor, Department of Electronics & Communication Engineering, DSATM, Bangalore
Manuscript received on January 26, 2020. | Revised Manuscript received on February 05, 2020. | Manuscript published on February 30, 2020. | PP: 2439-2441 | Volume-9 Issue-3, February 2020. | Retrieval Number: C5827029320/2020©BEIESP | DOI: 10.35940/ijeat.C5827.029320
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: In all ways of our life advance development in technology is growing. To expand the medical fields has become necessary, including the investigation on which action is made, by understanding the inner complicated arrangement of the abdominal organs example liver and exactly localizing the surface of the liver and its swelling, thereafter successful treatment will be done. Several numbers of algorithms projected to do the automatic liver segmentation. Different published works will be discussing here for liver segmentation. For each work the methods, datasets, outcomes and limitation will be discussing and conversing. A complete relative study is conducted here.
Keywords: Liver Segmentation, CT, CNN, FCN, Deep Learning, Machine Learning.