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

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...

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Detalles Bibliográficos
Autores principales: Vadmal, Vachan, Junno, Grant, Badve, Chaitra, Huang, William, Waite, Kristin A, Barnholtz-Sloan, Jill S
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7236385/
https://www.ncbi.nlm.nih.gov/pubmed/32642702
http://dx.doi.org/10.1093/noajnl/vdaa049
Descripción
Sumario: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.