Priscilla Machado, Aylin Tahmasebi, Samuel Fallon, Ji-Bin Liu, Basak E Dogan, Laurence Needleman, Melissa Lazar, Alliric I Willis, Kristin Brill, Susanna Nazarian, Adam Berger, Flemming Forsberg
The objective of the study was to use a deep learning model to differentiate between benign and malignant sentinel lymph nodes (SLNs) in patients with breast cancer compared to radiologists' assessments.Seventy-nine women with breast cancer were enrolled and underwent lymphosonography and contrast-enhanced ultrasound (CEUS) examination after subcutaneous injection of ultrasound contrast agent around their tumor to identify SLNs. Google AutoML was used to develop image classification model. Grayscale and CEUS images acquired during the ultrasound examination were uploaded with a data distribution of 80% for training/20% for testing...
September 1, 2024: Ultrasound Quarterly