Deep learning approach for discrimination of liver lesions using nine time-phase images of contrast-enhanced ultrasound.

Journal: Journal of medical ultrasonics (2001)
PMID: 38051461

Abstract

PURPOSE: Contrast-enhanced ultrasound (CEUS) shows different enhancement patterns depending on the time after administration of the contrast agent. The aim of this study was to evaluate the diagnostic performance of liver nodule characterization using our proposed deep learning model with input of nine CEUS images.

Authors

  • Naohisa Kamiyama
    Ultrasound General Imaging, GE HealthCare Japan, 127 Asahigaoka-4, Hino, Tokyo, 191-0065, Japan. naohisa.kamiyama@ge.com.
  • Katsutoshi Sugimoto
    Department of Gastroenterology and Hepatology, Tokyo Medical University, Tokyo, 160-0023, Japan.
  • Ryuichi Nakahara
    Science of Functional Recovery and Reconstruction, Graduate School of Medicine, Dentistry and Pharmaceu-tical Sciences, Okayama University, Okayama, Japan.
  • Tatsuya Kakegawa
    Department of Gastroenterology and Hepatology, Tokyo Medical University, Tokyo, 160-0023, Japan.
  • Takao Itoi
    Department of Gastroenterology and Hepatology, Tokyo Medical University, Tokyo, Japan.

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