Restricted Research - Award List, Note/Discussion Page

Fiscal Year: 2018

2015  The University of Texas at San Antonio  (75833)

Principal Investigator: Gibson, Matthew (Principal Investigator)  

Total Amount of Contract, Award, or Gift (Annual before 2011): $ 366,250

Exceeds $250,000 (Is it flagged?): Yes

Start and End Dates: 7/1/17 - 6/30/21

Restricted Research: YES

Academic Discipline: COS COMPUTER SCIENCE  

Department, Center, School, or Institute: COS COMPUTER SCIENCE  

Title of Contract, Award, or Gift: AitF: Collaborative Research: Automated Medical Image Segmentation via Object Decomposition

Name of Granting or Contracting Agency/Entity: Natl Science Fdn
CFDA Link: NSF
47.070

Program Title: N/A
CFDA Linked: Computer and Information Science and Engineering

Note:

Enormous technological advances have been made recently in biomedical imaging leading to a large amount of improved medical data, creating a demand for algorithms which can process this data faster and more thoroughly. Image segmentation, which aims to define accurate boundary surfaces for the objects of interest captured by image data, has been an indispensable tool in modern precision medicine for pathology detection, medical diagnosis, treatment planning, therapeutic response assessment and prognosis. In current clinical practice, this task is typically performed manually, on a slice-by-slice basis, with very limited support of automated tools. Following the seminal change in medicine heralded by the widespread use of volumetric imaging scanners, there is now a compelling need to overcome the inability of practicing physicians to efficiently and fully analyze the large amounts of medical image data generated by the acquisition devices, but reliable 3-D and 4-D segmentation methods allowing analysis of the image data in a quantitative manner with accurate, efficient, and robust performance in clinical practice are not available.

Discussion: No discussion notes

 

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