title: An energy minimization method for MS lesion segmentation from T1-w and FLAIR images.
abstract: In this paper, we extend the multiplicative intrinsic component optimization (MICO) algorithm to multichannel MR image segmentation, with focus on segmentation of multiple sclerosis (MS) lesions. The MICO algorithm was originally proposed by Li et al. in Ref. [1] for normal brain tissue segmentation and intensity inhomogeneity correction of a single channel MR image, which exhibits desirable advantages over other methods for MR image segmentation and intensity inhomogeneity correction in terms of segmentation accuracy and robustness. In this paper, we extend the MICO algorithm to multi-channel MR image segmentation and enable the segmentation of MS lesions. We assign different weights for different channels to control the impact of each channel. The weighted channels allow the enhancement of the impact of the FLAIR image on the segmentation of MS lesions by assigning a larger weight to the FLAIR image channel than the other channels. With the inherent mechanism of estimation of the bias field, our method is able to deal with the intensity inhomogeneity in the input multi-channel MR images. In the application of our method, we only use T1-w and FLAIR images as the input two channel MR images. Experimental results show promising result of our method.
authors.affiliation: School of Electronic Engineering, Jilin University, Changchun, Jilin, China.
authors.forename: Yue
authors.initials: Y
authors.lastname: Zhao
authors.affiliation: School of Electronic Engineering, Jilin University, Changchun, Jilin, China.
authors.forename: Shuxu
authors.initials: S
authors.lastname: Guo
authors.affiliation: Department of Radiology, Provincial Hospital of Fujian Province, Teaching Hospital of Fujian Medical University, Fuzhou, China.
authors.forename: Min
authors.initials: M
authors.lastname: Luo
authors.affiliation: School of Electronic Engineering, Jilin University, Changchun, Jilin, China.
authors.forename: Yu
authors.initials: Y
authors.lastname: Liu
authors.affiliation: Department of Radiology, University of Pennsylvania, Philadelphia 19104, USA.
authors.forename: Michel
authors.initials: M
authors.lastname: Bilello
authors.affiliation: School of Electronic Engineering, University of Electronic Science and Technology of China, Chengdu, Sichuan 611731, China. Electronic address: chunming.li@uestc.edu.cn.
authors.forename: Chunming
authors.initials: C
authors.lastname: Li
mesh_terms: D000465:Algorithms; D001921:Brain / Q000000981:diagnostic imaging* / Q000473:pathology; D006801:Humans; D007091:Image Processing, Computer-Assisted; D008279:Magnetic Resonance Imaging / Q000379:methods*; D009103:Multiple Sclerosis / Q000000981:diagnostic imaging* / Q000473:pathology
keywords: Bias field estimation; Lesion segmentation; Multichannel MR images; Multiple sclerosis lesion; Multiplicative intrinsic component optimization (MICO)