Liver Segmentation in Computed Tomography Abdomen Images Based on Particle Swarm Optimization and Morphology
S. Kiruthika1, I. Kaspar Raj2
1S.Kiruthika*, Research and Development Centre, Bharathiar University, Coimbatore, Tamil Nadu, India.
2Dr.I.Kaspar Raj, Director, Computer Centre, Gandhigram Rural Institute(Deemed to be University), Dindigul, Tamil Nadu, India.
Manuscript received on October 12, 2019. | Revised Manuscript received on 22 October, 2019. | Manuscript published on November 10, 2019. | PP: 2709-2713 | Volume-9 Issue-1, November 2019. | Retrieval Number: A4872119119/2019©BEIESP | DOI: 10.35940/ijitee.A4872.119119
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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: Segmenting liver from abdominal images is a thought-provoking task. A method for segmenting liver region from CT abdomen is proposed in this paper. Particle Swarm Optimization (PSO) method is employed for segmenting multiple regions in the abdomen image. Morphological operation such as Erosion and Dilation is used for segmenting exact portion of liver. Largest connected component and filling holes operation are applied as supporting techniques for image corrections. Experiment on our proposed segmentation approach is carried out and the results are discussed. The quantitative validation was performed with Dice similarity co-efficient metric.
Keywords: CT Liver, PSO, Morphology, Segmentation
Scope of the Article: Discrete Optimization