Automated Breast Ultrasound: Lesion Detection and BI-RADS™ Classification – a Pilot Study

Evelyn Wenkel; M Heckmann; Marc Heinrich; Siegfried A. Schwab; Michael Uder; R. Schulz-Wendtland; W Bautz; Rolf Janka

doi:10.1055/s-2008-1027563

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JOURNAL ARTICLE

Automated Breast Ultrasound: Lesion Detection and BI-RADS™ Classification – a Pilot Study

Evelyn Wenkel M Heckmann Marc Heinrich Siegfried A. Schwab Michael Uder R. Schulz-Wendtland W Bautz Rolf Janka

Year: 2008 Journal: RöFo - Fortschritte auf dem Gebiet der Röntgenstrahlen und der bildgebenden Verfahren Vol: 180 (09)Pages: 804-808 Publisher: Thieme Medical Publishers (Germany)

DOI: 10.1055/s-2008-1027563

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Abstract

These preliminary results show that the ABUS allows detection of solid and cystic lesions and their BI-RADS classification with a high reliability in a selected patient group.

Keywords:

Medicine Gynecology Nuclear medicine

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Topics

Breast Lesions and Carcinomas

Health Sciences → Medicine → Pathology and Forensic Medicine

AI in cancer detection

Physical Sciences → Computer Science → Artificial Intelligence

Breast Cancer Treatment Studies

Life Sciences → Biochemistry, Genetics and Molecular Biology → Cancer Research

Automated Breast Ultrasound: Lesion Detection and BI-RADS™ Classification – a Pilot Study

Abstract

Metrics

Citation History

Topics

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