Author name cluster
Possible papers associated with this exact author name in Arrow. This page groups case-insensitive exact name matches and is not a full identity disambiguation profile.
YNIMG Journal 2008 Journal Article
YNIMG Journal 2004 Journal Article
Accurate identification of brain tissue and cerebrospinal fluid (CSF) in a whole-head MRI is a critical first step in many neuroimaging studies. Automating this procedure can eliminate intra- and interrater variance and greatly increase throughput for a labor-intensive step. Many available procedures perform differently across anatomy and under different acquisition protocols. We developed the Brain Extraction Meta-Algorithm (BEMA) to address these concerns. It executes many extraction algorithms and a registration procedure in parallel to combine the results in an intelligent fashion and obtain improved results over any of the individual algorithms. Using an atlas space, BEMA performs a voxelwise analysis of training data to determine the optimal Boolean combination of extraction algorithms to produce the most accurate result for a given voxel. This allows the provided extractors to be used differentially across anatomy, increasing both the accuracy and robustness of the procedure. We tested BEMA using modified forms of BrainSuite's Brain Surface Extractor (BSE), FSL's Brain Extraction Tool (BET), AFNI's 3dIntracranial, and FreeSurfer's MRI Watershed as well as FSL's FLIRT for the registration procedure. Training was performed on T1-weighted scans of 136 subjects from five separate data sets with different acquisition parameters on separate scanners. Testing was performed on 135 separate subjects from the same data sets. BEMA outperformed the individual algorithms, as well as interrater results from a subset of the scans, when compared for the mean Dice coefficient, a rating of the similarity of output masks to the manually defined gold standards.
YNIMG Journal 2004 Journal Article
We used magnetic resonance imaging (MRI) and cortical pattern matching to map differences in cortical gray matter deficits between Alzheimer's disease (AD) and dementia with Lewy bodies (DLB), and explored the possible influence of gender on these patterns. Twenty-nine patients with AD (age 77. 9 ± 5. 5), 16 patients with DLB (76. 4 ± 6. 7), and 38 controls (75. 3 ± 6. 8) were included. Dementia groups were matched for illness severity. Detailed spatial analyses of gray matter were conducted across the entire cerebral cortex by measuring local proportions of gray matter at thousands of homologous cortical surface locations in each subject and between diagnostic groups. To visualize regional changes, statistical differences were mapped at each cortical surface location in 3D. Main effects of diagnosis demonstrated prominent gray matter differences in orbitofrontal and temporal cortices, where AD exhibited the greatest deficits relative to DLB. Main effects of sex showed less gray matter in men within all group comparisons. Exploratory findings for sex by diagnosis interactions suggest greater gray matter loss in the anterior cingulate for men with AD, relative to controls, AD females, and individuals with DLB. Relative preservation of orbitofrontal cortices in addition to temporal structures may contribute to distinguishing DLB from AD. Further investigation of the influence of gender might provide a more comprehensive understanding of the pathophysiological differences underlying the two forms of dementia.
YNIMG Journal 2001 Journal Article
YNIMG Journal 2001 Journal Article
YNIMG Journal 2001 Journal Article
YNIMG Journal 2001 Journal Article
YNIMG Journal 2000 Journal Article