• Neuroinformatics

Magnetic resonance imaging (MRI) segmentation is a fundamental and significant task since it can guide subsequent clinic diagnosis and treatment. However, images are often corrupted by defects such as low-contrast, noise, intensity inhomogeneity, and so on. Therefore, a weighted level set model (WLSM) is proposed in this study to segment inhomogeneous intensity MRI destroyed by noise and weak boundaries. First, in order to segment the intertwined regions of brain tissue accurately, a weighted neighborhood information measure scheme based on local multi information and kernel function is designed. Then, the membership function of fuzzy c-means clustering is used as the spatial constraint of level set model to overcome the sensitivity of level set to initialization, and the evolution of level set function can be adaptively changed according to different tissue information. Finally, the distance regularization term in level set function is replaced by a double potential function to ensure the stability of the energy function in the evolution process. Both real and synthetic MRI images can show the effectiveness and performance of WLSM. In addition, compared with several state-of-the-art models, segmentation accuracy and Jaccard similarity coefficient obtained by WLSM are increased by 0.0586, 0.0362 and 0.1087, 0.0703, respectively.

医学部小児科学教室　大澤眞木子教授退任記念特別号

Atrophy quantification is fundamental for understanding brain development and diagnosing and monitoring brain diseases. FSL-SIENA is a well-known fully automated method that has been widely used in brain magnetic resonance imaging studies. However, intensity variations arising during image acquisition may compromise evaluation, analysis and even diagnosis. In this work, we studied whether intensity standardisation could improve longitudinal atrophy quantification using FSL-SIENA. We evaluated the effect of six intensity standardisation methods—z-score, fuzzy c-means, Gaussian mixture model, kernel density estimation, histogram matching and WhiteStripe—on atrophy detected by FSL-SIENA. First, we evaluated scan–rescan repeatability using scans taken during the same session from OASIS (n=122). Except for WhiteStripe, intensity standardisation did not compromise the scan–rescan repeatability of FSL-SIENA. Second, we compared the mean annual atrophy for Alzheimer’s and control subjects from OASIS (n=122) and ADNI (n=147) yielded by FSL-SIENA with and without intensity standardisation, after adjusting for covariates. Our findings were threefold: First, the use of histogram matching was counterproductive, primarily as its assumption of equal tissue proportions does not necessarily hold in longitudinal studies. Second, standardising with z-score and WhiteStripe before registration affected the registration performance, thus leading to erroneous estimates. Third, z-score was the only method that consistently led to increased effect sizes compared to when omitted (no standardisation: 0.39 and 0.43 for OASIS and ADNI z-score: 0.45 for both datasets). Overall, we found that incorporating z-score right after registration led to reduced inter-subject inter-scan intensity variability and benefited FSL-SIENA. Our work evinces the relevance of appropriate intensity standardisation in longitudinal cerebral atrophy assessments using FSL-SIENA.

Al-Mosawi AJ. Von Recklinghausen syndrome with right-sided basal ganglion abnormalities on brain magnetic resonance imaging. Journal of Clinical Research in Radiology (ISSN: 2639-913X) 2019 Jan 20 ; 2 (1): 1-3. Doi: 10.5281/zenodo.4620619 https://asclepiusopen.com/journal-of-clinical-research-in-radiology/volume-2-issue-1/#