scispace - formally typeset
S

Sandhitsu R. Das

Researcher at University of Pennsylvania

Publications -  155
Citations -  6153

Sandhitsu R. Das is an academic researcher from University of Pennsylvania. The author has contributed to research in topics: Temporal lobe & Medicine. The author has an hindex of 32, co-authored 124 publications receiving 4672 citations. Previous affiliations of Sandhitsu R. Das include Hospital of the University of Pennsylvania.

Papers
More filters
Journal ArticleDOI

Multi-Atlas Segmentation with Joint Label Fusion

TL;DR: A new solution for the label fusion problem in which weighted voting is formulated in terms of minimizing the total expectation of labeling error and in which pairwise dependency between atlases is explicitly modeled as the joint probability of two atlas making a segmentation error at a voxel is proposed.
Journal ArticleDOI

Large-scale evaluation of ANTs and FreeSurfer cortical thickness measurements.

TL;DR: The largest evaluation of automated cortical thickness measures in publicly available data is conducted, comparing FreeSurfer and ANTs measures computed on 1205 images from four open data sets, with parcellation based on the recently proposed Desikan-Killiany-Tourville cortical labeling protocol.
Journal ArticleDOI

Automated Volumetry and Regional Thickness Analysis of Hippocampal Subfields and Medial Temporal Cortical Structures in Mild Cognitive Impairment

TL;DR: Thickness analysis results are consistent with volumetry, but provide additional regional specificity and suggest nonuniformity in the effects of aMCI on hippocampal subfields and MTL cortical subregions.
Journal ArticleDOI

Nearly Automatic Segmentation of Hippocampal Subfields in In Vivo Focal T2-Weighted MRI

TL;DR: The results support the feasibility of subfield-specific hippocampal morphometry in clinical studies of memory and neurodegenerative disease.
Journal ArticleDOI

Registration based cortical thickness measurement

TL;DR: A diffeomorphic registration based cortical thickness (DiReCT) measure is introduced where a continuous one-to-one correspondence between the gray matter-white matter interface and the estimatedgray matter-cerebrospinal fluid interface is given by a diffeomorph mapping in the image space.