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Journal of Imaging Informatics in Medicine

Published in:

01-02-2014

Computer-Aided Segmentation System for Breast MRI Tumour using Modified Automatic Seeded Region Growing (BMRI-MASRG)

Authors: Ali Qusay Al-Faris, Umi Kalthum Ngah, Nor Ashidi Mat Isa, Ibrahim Lutfi Shuaib

Published in: Journal of Imaging Informatics in Medicine | Issue 1/2014

Abstract

In this paper, an automatic computer-aided detection system for breast magnetic resonance imaging (MRI) tumour segmentation will be presented. The study is focused on tumour segmentation using the modified automatic seeded region growing algorithm with a variation of the automated initial seed and threshold selection methodologies. Prior to that, some pre-processing methodologies are involved. Breast skin is detected and deleted using the integration of two algorithms, namely the level set active contour and morphological thinning. The system is applied and tested on 40 test images from the RIDER breast MRI dataset, the results are evaluated and presented in comparison to the ground truths of the dataset. The analysis of variance (ANOVA) test shows that there is a statistically significance in the performance compared to the previous segmentation approaches that have been tested on the same dataset where ANOVA p values for the evaluation measures’ results are less than 0.05, such as: relative overlap (p = 0.0002), misclassification rate (p = 0.045), true negative fraction (p = 0.0001) and sum of true volume fraction (p = 0.0001).

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Title: Computer-Aided Segmentation System for Breast MRI Tumour using Modified Automatic Seeded Region Growing (BMRI-MASRG)
Authors: Ali Qusay Al-Faris
Umi Kalthum Ngah
Nor Ashidi Mat Isa
Ibrahim Lutfi Shuaib
Publication date: 01-02-2014
Publisher: Springer US
Published in: Journal of Imaging Informatics in Medicine / Issue 1/2014
Print ISSN: 2948-2925
Electronic ISSN: 2948-2933
DOI: https://doi.org/10.1007/s10278-013-9640-5

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Computer-Aided Segmentation System for Breast MRI Tumour using Modified Automatic Seeded Region Growing (BMRI-MASRG)

Abstract

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Abstract

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