ArticleMedical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention2016
Riemannian Statistical Analysis of Cortical Geometry with Robustness to Partial Homology and Misalignment.
Article in Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
3 citing papers in PubMed, 6 citations in OpenAlex.
- Predicting Cognitive Scores from Resting fMRI Data and Geometric Features of the Brain.Proceedings of SPIE--the International Society for Optical Engineering · 2019Article
- A Comparative Atlas-Based Recognition of Mild Cognitive Impairment With Voxel-Based Morphometry.Frontiers in neuroscience · 2018Article
- Kernel Methods for Riemannian Analysis of Robust Descriptors of the Cerebral Cortex.Information processing in medical imaging : proceedings of the ... conference · 2017Article
Corrections and comments
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Authors and funding
3 authors at 2 institutions in 2 countries.
Funding
Abstract
Typical studies of the geometry of the cerebral cortical structure focus on either cortical folding or thickness. They rely on spatial normalization, but use cortical descriptors that are sensitive to misregistration arising from the well-known problems of partial homologies between subject brains and local optima in nonlinear registration. In contrast to these approaches, we propose a novel framework for studying the geometry of the
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.