Accepted Manuscript

Development of a Combinational Framework to Concurrently PerformTissue Segmentation and Tumor Identification in T1 - W, T2 - W,FLAIR and MPR type Magnetic Resonance Brain Images

Anitha Vishnuvarthanan , M. Pallikonda Rajasekaran ,Vishnuvarthanan Govindaraj , Yudong Zhang ,Arunprasath Thiyagarajan

PII: S0957-4174(17)30796-0DOI: 10.1016/j.eswa.2017.11.040Reference: ESWA 11683

To appear in: Expert Systems With Applications

Received date: 9 August 2017Revised date: 15 October 2017Accepted date: 16 November 2017

Please cite this article as: Anitha Vishnuvarthanan , M. Pallikonda Rajasekaran ,Vishnuvarthanan Govindaraj , Yudong Zhang , Arunprasath Thiyagarajan , Development of aCombinational Framework to Concurrently Perform Tissue Segmentation and Tumor Identificationin T1 - W, T2 - W, FLAIR and MPR type Magnetic Resonance Brain Images, Expert Systems WithApplications (2017), doi: 10.1016/j.eswa.2017.11.040

This is a PDF file of an unedited manuscript that has been accepted for publication. As a serviceto our customers we are providing this early version of the manuscript. The manuscript will undergocopyediting, typesetting, and review of the resulting proof before it is published in its final form. Pleasenote that during the production process errors may be discovered which could affect the content, andall legal disclaimers that apply to the journal pertain.

https://doi.org/10.1016/j.eswa.2017.11.040https://doi.org/10.1016/j.eswa.2017.11.040

ACCEPTED MANUSCRIPT

ACCE

PTED

MAN

USCR

IPT

1

Highlights

Development of a novel combinatorial technique for MR brain image analysis.

Achieving simultaneous tumor detection and tissue segmentation using an automated algorithm.

Minimal time duration and lesser manual intervention for segmenting the input MR brain images.

A dynamic algorithm for identifying the heterogeneous tumor regions.

A vivid comparison made for proving the efficacy of the proposed BFOA based MFCM methodology.

https://isiarticles.com/article/142835