Universal Fast Marching Method to Identify Liver Image

Liver segmentation is of prime importance in modern liver disease diagnosis and analysis. In our paper, random section of liver image is chosen and its histogram is achieved. From histogram, liver pixel intensity range is obtained. Using the range value, threshold segmentation is carried out which d...

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Bibliographic Details
Published inIOP conference series. Materials Science and Engineering Vol. 925; no. 1; pp. 12032 - 12041
Main Authors Siri, Sangeeta K, Pramod Kumar, S, Gavisiddappa
Format Journal Article
LanguageEnglish
Published Bristol IOP Publishing 01.09.2020
Subjects
Algorithms
Computed Tomography
Fast Marching Method
Histograms
Identification methods
Image segmentation
Liver
Liver segmentation
Magnetic Resonance Imaging
Medical imaging
Organs
threshold based segmentation
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Summary:Liver segmentation is of prime importance in modern liver disease diagnosis and analysis. In our paper, random section of liver image is chosen and its histogram is achieved. From histogram, liver pixel intensity range is obtained. Using the range value, threshold segmentation is carried out which detaches the liver from its adjoining organs. Median filter is employed to curtail the noise. The sigmoidal function is applied to improve anatomical structures of image. Then the image is converted into binary called as speed function. The novel algorithm is designed to locate the start points within speed function without user intervention. These start point evolved outwardly using Fast Marching Method till complete periphery of liver is reached. The proposed algorithm is compared with popularly used segmentation algorithms. The results show that proposed segmentation algorithm is robust in approach.
ISSN:1757-8981
1757-899X
DOI:10.1088/1757-899X/925/1/012032