Computer-Aided Diagnosis of Focal Liver Lesions Using Contrast-Enhanced Ultrasonography With Perflubutane Microbubbles

• Published in: IEEE transactions on medical imaging Vol. 36; no. 7; pp. 1427 - 1437
• Main Authors: Kondo, Satoshi, Takagi, Kazuya, Nishida, Mutsumi, Iwai, Takahito, Kudo, Yusuke, Ogawa, Kouji, Kamiyama, Toshiya, Shibuya, Hitoshi, Kahata, Kaoru, Shimizu, Chikara
• Format: Journal Article
• Language: English
• Published: United States IEEE 01.07.2017; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Benign; Classification; Computer-aided diagnosis; Contrast agents; Contrast Media; contrast-enhanced ultrasonography; Dependence; Fluorocarbons; focal liver lesion; Frequency locked loops; Hepatocellular carcinoma; Humans; Learning algorithms; Lesions; Liver; Liver Neoplasms; Machine learning; Medical diagnosis; Metastases; Metastasis; Microbubbles; Portals; Sensitivity; support vector machine; Support vector machines; Temporal variations; time intensity curve; Tumors; Ultrasonic imaging; Ultrasonography; Ultrasound

This paper proposes an automatic classification method based on machine learning in contrast-enhanced ultrasonography (CEUS) of focal liver lesions using the contrast agent Sonazoid. This method yields spatial and temporal features in the arterial phase, portal phase, and post-vascular phase, as wel...