MRI image analysis methods and applications: an algorithmic perspective using brain tumors as an exemplar

Author:

Vadmal Vachan1,Junno Grant1,Badve Chaitra2,Huang William1,Waite Kristin A134,Barnholtz-Sloan Jill S13564ORCID

Affiliation:

1. Department of Population Health and Quantitative Sciences, Case Western Reserve University School of Medicine, Cleveland, Ohio

2. Department of Radiology, University Hospitals Health System (UHHS), Cleveland, Ohio

3. Cleveland Center for Health Outcomes Research (CCHOR), Cleveland, Ohio

4. Cleveland Institute for Computational Biology, Cleveland, Ohio

5. Research Health Analytics and Informatics, UHHS, Cleveland, Ohio

6. Case Comprehensive Cancer Center, Cleveland, Ohio

Abstract

Abstract The use of magnetic resonance imaging (MRI) in healthcare and the emergence of radiology as a practice are both relatively new compared with the classical specialties in medicine. Having its naissance in the 1970s and later adoption in the 1980s, the use of MRI has grown exponentially, consequently engendering exciting new areas of research. One such development is the use of computational techniques to analyze MRI images much like the way a radiologist would. With the advent of affordable, powerful computing hardware and parallel developments in computer vision, MRI image analysis has also witnessed unprecedented growth. Due to the interdisciplinary and complex nature of this subfield, it is important to survey the current landscape and examine the current approaches for analysis and trend trends moving forward.

Funder

CWRU School of Medicine and University Hospitals Research Division

Publisher

Oxford University Press (OUP)

Subject

Electrical and Electronic Engineering,Building and Construction

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