Evaluating Reliability of Performance Metrics for Bias Field Correction in MR Brain Images
نویسندگان
چکیده
Introduction. Performance of nonuniformity correction approaches is usually evaluated indirectly, on the basis of remaining tissue intensity variability rather than the actual estimated bias field. Common indirect measures include coefficient of variation of white matter CV(WM) and gray matter CV(GM), and coefficient of joint variation CJV between WM and GM [1]. However, disagreements between indirect measures on what is the best performing method, reported in several recent studies [2,3], suggest that indirect measures might not reliably reflect the true nonuniformity correction performance. Here we examined reliability of several common performance measures using simulated brain data.
منابع مشابه
Quantitative Comparison of SPM, FSL, and Brainsuite for Brain MR Image Segmentation
Background: Accurate brain tissue segmentation from magnetic resonance (MR) images is an important step in analysis of cerebral images. There are software packages which are used for brain segmentation. These packages usually contain a set of skull stripping, intensity non-uniformity (bias) correction and segmentation routines. Thus, assessment of the quality of the segmented gray matter (GM), ...
متن کاملComparison of state-of-the-art atlas-based bone segmentation approaches from brain MR images for MR-only radiation planning and PET/MR attenuation correction
Introduction: Magnetic Resonance (MR) imaging has emerged as a valuable tool in radiation treatment (RT) planning as well as Positron Emission Tomography (PET) imaging owing to its superior soft-tissue contrast. Due to the fact that there is no direct transformation from voxel intensity in MR images into electron density, itchr('39')s crucial to generate a pseudo-CT (Computed Tomography) image ...
متن کاملEvaluation of performance metrics for bias field correction in MR brain images.
PURPOSE To investigate inconsistencies between common performance measures for bias field correction reported in several recent studies and propose a solution. MATERIALS AND METHODS A set of synthetic images of a normal brain from the Montréal Simulated Brain Database (SBD) was processed using two bias field correction algorithms. The parameters of these algorithms were varied and the resulti...
متن کاملروشی نوین در کاهش نوفه رایسین از مقدار بزرگی سیگنال دیفیوژن در تصویربرداری تشدید مغناطیسی (MRI)
The true MR signal intensity extracted from noisy MR magnitude images is biased with the Rician noise caused by noise rectification in the magnitude calculation for low intensity pixels. This noise is more problematic when a quantitative analysis is performed based on the magnitude images with low SNR(<3.0). In such cases, the received signal for both the real and imaginary components will fluc...
متن کاملMethod for bias field correction of brain T1-weighted magnetic resonance images minimizing segmentation error.
This work presents a new algorithm (nonuniform intensity correction; NIC) for correction of intensity inhomogeneities in T1-weighted magnetic resonance (MR) images. The bias field and a bias-free image are obtained through an iterative process that uses brain tissue segmentation. The algorithm was validated by means of realistic phantom images and a set of 24 real images. The first evaluation p...
متن کامل