scholarly journals PATHOLOGICAL BRAIN DETECTION BY ARTIFICIAL INTELLIGENCE IN MAGNETIC RESONANCE IMAGING SCANNING (INVITED REVIEW)

2016 ◽  
Vol 156 ◽  
pp. 105-133 ◽  
Author(s):  
Shuihua Wang ◽  
Yin Zhang ◽  
Tianmin Zhan ◽  
Preetha Phillips ◽  
Yudong Zhang ◽  
...  
2020 ◽  
Vol 24 (01) ◽  
pp. 021-029 ◽  
Author(s):  
Elisabeth R. Garwood ◽  
Ryan Tai ◽  
Ganesh Joshi ◽  
George J. Watts V

AbstractArtificial intelligence (AI) holds the potential to revolutionize the field of radiology by increasing the efficiency and accuracy of both interpretive and noninterpretive tasks. We have only just begun to explore AI applications in the diagnostic evaluation of knee pathology. Experimental algorithms have already been developed that can assess the severity of knee osteoarthritis from radiographs, detect and classify cartilage lesions, meniscal tears, and ligament tears on magnetic resonance imaging, provide automatic quantitative assessment of tendon healing, detect fractures on radiographs, and predict those at highest risk for recurrent bone tumors. This article reviews and summarizes the most current literature.


Heart Rhythm ◽  
2013 ◽  
Vol 10 (12) ◽  
pp. 1815-1821 ◽  
Author(s):  
Bruce L. Wilkoff ◽  
Timothy Albert ◽  
Mariya Lazebnik ◽  
Sung-Min Park ◽  
Jonathan Edmonson ◽  
...  

Heart Rhythm ◽  
2015 ◽  
Vol 12 (6) ◽  
pp. 1183-1191 ◽  
Author(s):  
William M. Bailey ◽  
Lawrence Rosenthal ◽  
Lameh Fananapazir ◽  
Marye Gleva ◽  
Alexander Mazur ◽  
...  

Sign in / Sign up

Export Citation Format

Share Document