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Segmentation of Liver from Abdomen CT Images Using Classification and Regression Tree

T.R. Nisha Dayana1 , A. Lenin Fred2

Section:Research Paper, Product Type: Journal Paper
Volume-7 , Issue-1 , Page no. 327-332, Jan-2019

CrossRef-DOI:   https://doi.org/10.26438/ijcse/v7i1.327332

Online published on Jan 31, 2019

Copyright © T.R. Nisha Dayana, A. Lenin Fred . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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IEEE Style Citation: T.R. Nisha Dayana, A. Lenin Fred, “Segmentation of Liver from Abdomen CT Images Using Classification and Regression Tree,” International Journal of Computer Sciences and Engineering, Vol.7, Issue.1, pp.327-332, 2019.

MLA Style Citation: T.R. Nisha Dayana, A. Lenin Fred "Segmentation of Liver from Abdomen CT Images Using Classification and Regression Tree." International Journal of Computer Sciences and Engineering 7.1 (2019): 327-332.

APA Style Citation: T.R. Nisha Dayana, A. Lenin Fred, (2019). Segmentation of Liver from Abdomen CT Images Using Classification and Regression Tree. International Journal of Computer Sciences and Engineering, 7(1), 327-332.

BibTex Style Citation:
@article{Dayana_2019,
author = {T.R. Nisha Dayana, A. Lenin Fred},
title = {Segmentation of Liver from Abdomen CT Images Using Classification and Regression Tree},
journal = {International Journal of Computer Sciences and Engineering},
issue_date = {1 2019},
volume = {7},
Issue = {1},
month = {1},
year = {2019},
issn = {2347-2693},
pages = {327-332},
url = {https://www.ijcseonline.org/full_paper_view.php?paper_id=3506},
doi = {https://doi.org/10.26438/ijcse/v7i1.327332}
publisher = {IJCSE, Indore, INDIA},
}

RIS Style Citation:
TY - JOUR
DO = {https://doi.org/10.26438/ijcse/v7i1.327332}
UR - https://www.ijcseonline.org/full_paper_view.php?paper_id=3506
TI - Segmentation of Liver from Abdomen CT Images Using Classification and Regression Tree
T2 - International Journal of Computer Sciences and Engineering
AU - T.R. Nisha Dayana, A. Lenin Fred
PY - 2019
DA - 2019/01/31
PB - IJCSE, Indore, INDIA
SP - 327-332
IS - 1
VL - 7
SN - 2347-2693
ER -

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Abstract

Segmentation role is inevitable in image processing for the extraction of the desired region of interest. This work proposes decision tree for the segmentation of liver from abdomen CT images. Prior to feature extraction and segmentation, feature extraction was performed by the median filter. The hybrid feature extraction comprising of GLCM and LBP is used and training phase comprises of 20 DICOM CT abdomen images. The morphological operations are performed in the post processing phase for the refinement of output. The algorithms are developed in Matlab 2010a and tested on real time abdomen CT images.

Key-Words / Index Term

Decision tree; Segmentation; Classification, regression tree

References

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