Thursday, July 3, 2025 7/3/2025

Novel Construction of Unbiased Templates for Brain Morphometry

Award Number: R03MH120627
ORGANIZATION: NATIONAL INSTITUTE OF MENTAL HEALTH
OPDIV: NIH
AWARD CLASS: DISCRETIONARY
AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)
PERIOD OF PERFORMANCE START DATE: 05/20/2020
PERIOD OF PERFORMANCE END DATE: 05/19/2023

Group Awards By:

View Award Description

Novel Construction of Unbiased Templates for Brain Morphometry - Summary (11/16/2019) In this project, we develop novel computational methods for image analysis with applications in brain structure variability studies. The proposed methods are based on a new Variational Principle which constructs a deformation with prescribed Jacobian determinant (which models local tissue size changes) and prescribed curl vector (which models local rotations). The goal of this research is to convince the medical image researchers and users that Jacobian determinant as well as curl vector should both be used in all steps of image analysis. Specifically, we develop: (1) A method of averaging a set of deformations based on Jacobian determinants and the curl vectors; the new method constructs the average as a deformation whose Jacobian determinant is equal to the average of the Jacobian determinants and whose curl vector is the average of curl vectors. This new method is biologically meaningful; it also preserves invertibilty of the deformations in the set. (2) A general robust method for construction of unbiased templates from a set of images. The method begins with registering a randomly chosen image in the set to all images in the set. Then the resample of the initial template on the average of the registration deformations is a good approximation; but it may still be biased toward the initial template. We then repeat the averaging process to remove bias and obtain unbiased template. Computational examples are presented to show the effects of curl vector and the effectiveness of method for averaging deformations and our method for construction of unbiased template. The project will significantly enhance our ability to analyze brain image data; improve diagnosis, monitor , and treatment of brain diseases and mental disorder. The project has an important training and educational component. Specifically, a PhD student will participate in algorithm design, computer code development, testing, and software management.


Issue Date FY	Funding FY	Legal Entity Name	Legal Entity Address	Legal Entity City	Legal Entity State	Legal Entity Zip Code	Legal Entity COUNTY	Legal Entity COUNTRY	Assistance Listing	Award Code	Budget Year	Action Date	Action Type	Action Amount

Issue Date FY: 2024 ( Subtotal = -$15,635 )
2024	2020	UNIVERSITY OF TEXAS AT ARLINGTON	701 S NEDDERMAN DR	ARLINGTON	TX	76019	TARRANT	USA	Mental Health Research Grants	000	1	1/24/2024	NEW	-$15,635
														Subtotal = -$15,635

Issue Date FY: 2020 ( Subtotal = $152,385 )
2020	2020	UNIVERSITY OF TEXAS AT ARLINGTON	400 S CORN ST	ARLINGTON	TX	76019	TARRANT	USA	Mental Health Research Grants	000	1	5/19/2020	NEW	$152,385
														Subtotal = $152,385

Grand Total All Awards = $136,750

Top

All Categories

About

Search

Reports

Data Submission

Award Information

Novel Construction of Unbiased Templates for Brain Morphometry

Award Number: R03MH120627

ORGANIZATION: NATIONAL INSTITUTE OF MENTAL HEALTH

OPDIV: NIH

AWARD CLASS: DISCRETIONARY

AWARD ACTIVITY TYPE: SCIENTIFIC/HEALTH RESEARCH (INCLUDES SURVEYS)

PERIOD OF PERFORMANCE START DATE: 05/20/2020

PERIOD OF PERFORMANCE END DATE: 05/19/2023

Federal Websites

Department of Health & Human Services

HHS Operating Divisions

HHS Staff Divisions

Download A Document Viewer