Liver Segmentation using Bidirectional Region Growing with Edge Enhancement in NSCT Domain

B. Lakshmipriya; K. Jayanthi; Biju Pottakkat; G. Ramkumar

doi:10.1109/ICSCAN.2018.8541257

Liver Segmentation using Bidirectional Region Growing with Edge Enhancement in NSCT Domain

B. Lakshmipriya, K. Jayanthi, Biju Pottakkat, G. Ramkumar

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

6 Scopus citations

Abstract

Segmentation of liver from abdominal CT image seems to be a challenging task in the computer aided diagnosis of liver pathology. This is due to the fact that liver and the adjacent organs in the CT image possess similar intensity attributes. In this work, a semi-Automatic segmentation of liver is carried out through bidirectional region based segmentation. Prior to segmentation, the edge regions of the liver are enhanced by means of unsharp masking in Non Sub-sampled Contourlet Transform (NSCT) domain. This ensures that there is a precise differentiation between the liver region and the adjacent organs and other structures like ribs. From the acquired results, it is clear that the combination of bidirectional region growing segmentation and edge enhancement in NSCT domain outperforms the segmentation by region growing algorithm and bidirectional region growing algorithm without edge enhancement.

Original language	English
Title of host publication	2018 IEEE International Conference on System, Computation, Automation and Networking, ICSCA 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)	9781538648667
DOIs	https://doi.org/10.1109/ICSCAN.2018.8541257
State	Published - Nov 20 2018
Externally published	Yes
Event	2018 IEEE International Conference on System, Computation, Automation and Networking, ICSCA 2018 - Pondicherry, India Duration: Jul 6 2018 → Jul 7 2018

Publication series

Name	2018 IEEE International Conference on System, Computation, Automation and Networking, ICSCA 2018

Conference

Conference	2018 IEEE International Conference on System, Computation, Automation and Networking, ICSCA 2018
Country/Territory	India
City	Pondicherry
Period	07/6/18 → 07/7/18

Funding

This work is supported by the University Commission (UGC), India under Minor Research scheme. [Grant No.F 6684/16].

Keywords

Bidirectional region growing
Edge enhancement
Non sub-sampled contourlet transform
Segmentation

Access to Document

10.1109/ICSCAN.2018.8541257

Cite this

Lakshmipriya, B., Jayanthi, K., Pottakkat, B., & Ramkumar, G. (2018). Liver Segmentation using Bidirectional Region Growing with Edge Enhancement in NSCT Domain. In 2018 IEEE International Conference on System, Computation, Automation and Networking, ICSCA 2018 Article 8541257 (2018 IEEE International Conference on System, Computation, Automation and Networking, ICSCA 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/ICSCAN.2018.8541257

Lakshmipriya, B. ; Jayanthi, K. ; Pottakkat, Biju et al. / Liver Segmentation using Bidirectional Region Growing with Edge Enhancement in NSCT Domain. 2018 IEEE International Conference on System, Computation, Automation and Networking, ICSCA 2018. Institute of Electrical and Electronics Engineers Inc., 2018. (2018 IEEE International Conference on System, Computation, Automation and Networking, ICSCA 2018).

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title = "Liver Segmentation using Bidirectional Region Growing with Edge Enhancement in NSCT Domain",

abstract = "Segmentation of liver from abdominal CT image seems to be a challenging task in the computer aided diagnosis of liver pathology. This is due to the fact that liver and the adjacent organs in the CT image possess similar intensity attributes. In this work, a semi-Automatic segmentation of liver is carried out through bidirectional region based segmentation. Prior to segmentation, the edge regions of the liver are enhanced by means of unsharp masking in Non Sub-sampled Contourlet Transform (NSCT) domain. This ensures that there is a precise differentiation between the liver region and the adjacent organs and other structures like ribs. From the acquired results, it is clear that the combination of bidirectional region growing segmentation and edge enhancement in NSCT domain outperforms the segmentation by region growing algorithm and bidirectional region growing algorithm without edge enhancement.",

keywords = "Bidirectional region growing, Edge enhancement, Non sub-sampled contourlet transform, Segmentation",

author = "B. Lakshmipriya and K. Jayanthi and Biju Pottakkat and G. Ramkumar",

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Lakshmipriya, B, Jayanthi, K, Pottakkat, B & Ramkumar, G 2018, Liver Segmentation using Bidirectional Region Growing with Edge Enhancement in NSCT Domain. in 2018 IEEE International Conference on System, Computation, Automation and Networking, ICSCA 2018., 8541257, 2018 IEEE International Conference on System, Computation, Automation and Networking, ICSCA 2018, Institute of Electrical and Electronics Engineers Inc., 2018 IEEE International Conference on System, Computation, Automation and Networking, ICSCA 2018, Pondicherry, India, 07/6/18. https://doi.org/10.1109/ICSCAN.2018.8541257

Liver Segmentation using Bidirectional Region Growing with Edge Enhancement in NSCT Domain. / Lakshmipriya, B.; Jayanthi, K.; Pottakkat, Biju et al.
2018 IEEE International Conference on System, Computation, Automation and Networking, ICSCA 2018. Institute of Electrical and Electronics Engineers Inc., 2018. 8541257 (2018 IEEE International Conference on System, Computation, Automation and Networking, ICSCA 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AU - Jayanthi, K.

AU - Pottakkat, Biju

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PY - 2018/11/20

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N2 - Segmentation of liver from abdominal CT image seems to be a challenging task in the computer aided diagnosis of liver pathology. This is due to the fact that liver and the adjacent organs in the CT image possess similar intensity attributes. In this work, a semi-Automatic segmentation of liver is carried out through bidirectional region based segmentation. Prior to segmentation, the edge regions of the liver are enhanced by means of unsharp masking in Non Sub-sampled Contourlet Transform (NSCT) domain. This ensures that there is a precise differentiation between the liver region and the adjacent organs and other structures like ribs. From the acquired results, it is clear that the combination of bidirectional region growing segmentation and edge enhancement in NSCT domain outperforms the segmentation by region growing algorithm and bidirectional region growing algorithm without edge enhancement.

AB - Segmentation of liver from abdominal CT image seems to be a challenging task in the computer aided diagnosis of liver pathology. This is due to the fact that liver and the adjacent organs in the CT image possess similar intensity attributes. In this work, a semi-Automatic segmentation of liver is carried out through bidirectional region based segmentation. Prior to segmentation, the edge regions of the liver are enhanced by means of unsharp masking in Non Sub-sampled Contourlet Transform (NSCT) domain. This ensures that there is a precise differentiation between the liver region and the adjacent organs and other structures like ribs. From the acquired results, it is clear that the combination of bidirectional region growing segmentation and edge enhancement in NSCT domain outperforms the segmentation by region growing algorithm and bidirectional region growing algorithm without edge enhancement.

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Lakshmipriya B, Jayanthi K, Pottakkat B, Ramkumar G. Liver Segmentation using Bidirectional Region Growing with Edge Enhancement in NSCT Domain. In 2018 IEEE International Conference on System, Computation, Automation and Networking, ICSCA 2018. Institute of Electrical and Electronics Engineers Inc. 2018. 8541257. (2018 IEEE International Conference on System, Computation, Automation and Networking, ICSCA 2018). doi: 10.1109/ICSCAN.2018.8541257

Liver Segmentation using Bidirectional Region Growing with Edge Enhancement in NSCT Domain

Abstract

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Keywords

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