Radiol Artif Intell 2021 Jan 2;3(1):e200125. Epub 2020 Dec 2.
Department of Radiology, Division of Musculoskeletal Radiology, NYU Langone Health, 301 E 17th St, 6th Floor, New York, NY, 10003 (B.W., C.B., R.S.A.); and Department of Musculoskeletal Imaging, Hôpital Lariboisière, Paris, France (L.P.).
Purpose: To train convolutional neural network (CNN) models to classify benign and malignant soft-tissue masses at US and to differentiate three commonly observed benign masses.
Materials And Methods: In this retrospective study, US images obtained between May 2010 and June 2019 from 419 patients (mean age, 52 years ± 18 [standard deviation]; 250 women) with histologic diagnosis confirmed at biopsy or surgical excision ( = 227) or masses that demonstrated imaging characteristics of lipoma, benign peripheral nerve sheath tumor, and vascular malformation ( = 192) were included. Images in patients with a histologic diagnosis ( = 227) were used to train and evaluate a CNN model to distinguish malignant and benign lesions. Read More