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Automatic Segmentation of Liver Lesion from Ultrasound Images


Affiliations
1 Sathyabama University, Chennai-600119, India
2 Anna University, Chennai-600025, India
     

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In this study, we focus on liver lesion Segmentation from ultrasound images using Region Growing algorithm with texture features parameters on spatial information. Segmentation of Ultrasound liver lesion is very challenging due to low contrast nature of image and occurrence of speckle noise. Liver cancer is the fifth most common cancer worldwide in men and eighth in women, and is one of the few cancers still on the rise. The goal of our study is that Region growing with texture parameters in gray space map on spatial information algorithm is supporting better for segmenting ultrasound liver lesion.

Keywords

Ultrasound Liver Lesion, Region Growing, Thresholding, Segmentation, Gray Space Map.
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  • Automatic Segmentation of Liver Lesion from Ultrasound Images

Abstract Views: 204  |  PDF Views: 5

Authors

V. Ulagamuthalvi
Sathyabama University, Chennai-600119, India
D. Sridharan
Anna University, Chennai-600025, India

Abstract


In this study, we focus on liver lesion Segmentation from ultrasound images using Region Growing algorithm with texture features parameters on spatial information. Segmentation of Ultrasound liver lesion is very challenging due to low contrast nature of image and occurrence of speckle noise. Liver cancer is the fifth most common cancer worldwide in men and eighth in women, and is one of the few cancers still on the rise. The goal of our study is that Region growing with texture parameters in gray space map on spatial information algorithm is supporting better for segmenting ultrasound liver lesion.

Keywords


Ultrasound Liver Lesion, Region Growing, Thresholding, Segmentation, Gray Space Map.