Development of a combinational framework to concurrently perform tissue segmentation and tumor identification in T1 - W, T2 - W, FLAIR and MPR type magnetic resonance brain images
作者：
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.
摘要
•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.
论文关键词：MR brain image segmentation,Bacteria foraging optimization,Modified Fuzzy C-Means algorithm,Tumor detection,Tissue segmentation
论文评审过程：Received 9 August 2017, Revised 15 October 2017, Accepted 16 November 2017, Available online 21 November 2017, Version of Record 14 December 2017.
论文官网地址：https://doi.org/10.1016/j.eswa.2017.11.040
