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Current Status of Radiomics and Deep Learning in Liver Imaging.
Chu, Linda C; Park, Seyoun; Kawamoto, Satomi; Yuille, Alan L; Hruban, Ralph H; Fishman, Elliot K.
Affiliation
  • Chu LC; From the The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins Hospital, Johns Hopkins University School of Medicine.
  • Park S; From the The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins Hospital, Johns Hopkins University School of Medicine.
  • Kawamoto S; From the The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins Hospital, Johns Hopkins University School of Medicine.
  • Yuille AL; Department of Computer Science, Johns Hopkins University.
  • Hruban RH; Sol Goldman Pancreatic Cancer Research Center, Department of Pathology, Johns Hopkins University School of Medicine, Baltimore, MD.
  • Fishman EK; From the The Russell H. Morgan Department of Radiology and Radiological Science, The Johns Hopkins Hospital, Johns Hopkins University School of Medicine.
J Comput Assist Tomogr ; 45(3): 343-351, 2021.
Article in En | MEDLINE | ID: mdl-34297507
ABSTRACT: Artificial intelligence is poised to revolutionize medical image. It takes advantage of the high-dimensional quantitative features present in medical images that may not be fully appreciated by humans. Artificial intelligence has the potential to facilitate automatic organ segmentation, disease detection and characterization, and prediction of disease recurrence. This article reviews the current status of artificial intelligence in liver imaging and reviews the opportunities and challenges in clinical implementation.
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Radiographic Image Interpretation, Computer-Assisted / Liver Neoplasms Limits: Humans Language: En Journal: J Comput Assist Tomogr Year: 2021 Type: Article
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Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Radiographic Image Interpretation, Computer-Assisted / Liver Neoplasms Limits: Humans Language: En Journal: J Comput Assist Tomogr Year: 2021 Type: Article