Proceedings ArticleDOI
MS Lesion Segmentation for Single and Multichannel MRI Images Using MICO Technique
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TLDR
The multiplicative intrinsic component optimization technique was able to solve the problem of intensity inhomogeneity through bias field estimation and correction and followed by lesion segmentation and showed better and promising results when compared to ground truth images.Abstract:
We Implement multiplicative intrinsic component optimization technique to single and multichannel MRI images for segmenting multiple sclerosis lesions. This technique solves the problem of intensity inhomogeneity by estimating and correcting bias field. In segmentation it has more advantages over other MS lesion segmentation techniques in terms of precision. In multichannel segmentation, distinct weights are given for different channels to regulate the effect of each channel output. We use T1-w and FLAIR images in the multichannel segmentation of MS lesions. we provide higher weight to FLAIR images as they regulate in enhancing the segmented lesions. we were able to solve the problem of intensity inhomogeneity through bias field estimation and correction and followed by lesion segmentation. Our technique showed better and promising results when compared to ground truth images.read more
Citations
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Journal ArticleDOI
Segmentation and Analysis Emphasizing Neonatal MRI Brain Images Using Machine Learning Techniques
Saritha Saladi,Yepuganti Karuna,Srinivas Koppu,G.R. Reddy,Senthilkumar Mohan,Saurav Mallik,Hong Qin +6 more
TL;DR: In this paper , the authors proposed a novel ARKFCM to use for segmentation of brain tumor in neonatal brain using HE, CLAHE, and BPDFHE enhancement techniques.
References
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Journal ArticleDOI
Automated segmentation of multiple sclerosis lesions by model outlier detection
TL;DR: A fully automated algorithm for segmentation of multiple sclerosis lesions from multispectral magnetic resonance (MR) images that performs intensity-based tissue classification using a stochastic model and simultaneously detects MS lesions as outliers that are not well explained by the model.
Journal ArticleDOI
A topology-preserving approach to the segmentation of brain images with multiple sclerosis lesions.
TL;DR: Evaluation with both simulated and real data sets demonstrates that the method has an accuracy competitive with state-of-the-art MS lesion segmentation methods, while simultaneously segmenting the whole brain.
Journal ArticleDOI
Multiplicative intrinsic component optimization (MICO) for MRI bias field estimation and tissue segmentation
TL;DR: The MICO formulation can be naturally extended to 3D/4D tissue segmentation with spatial/sptatiotemporal regularization and the energy in the formulation is convex in each of its variables, which leads to the robustness of the proposed energy minimization algorithm.
Journal ArticleDOI
Segmentation of multiple sclerosis lesions in brain MRI: A review of automated approaches
Xavier Lladó,Arnau Oliver,Mariano Cabezas,Jordi Freixenet,Joan C. Vilanova,Ana Quiles,Laia Valls,Lluís Ramió-Torrentí,ílex Rovira +8 more
TL;DR: The main features of the segmentation algorithms are analysed and the most recent important techniques are classified into different strategies according to their main principle, pointing out their strengths and weaknesses and suggesting new research directions.
Journal ArticleDOI
Impact of White Matter Changes on Clinical Manifestation of Alzheimer’s Disease A Quantitative Study
TL;DR: The hypothesis that WMHs in AD patients are superimposed phenomena of vascular origin that contribute to specific neurological and neuropsychiatric manifestations but not to global cognitive impairment, which is more closely associated with brain atrophy is supported.
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