CPC A61B 8/085 (2013.01) [A61B 8/485 (2013.01); A61B 8/488 (2013.01); A61B 8/5223 (2013.01); G06N 3/045 (2023.01); G06N 3/084 (2013.01)] | 20 Claims |
1. A system for automatically diagnosing thyroid nodules, the system comprising:
at least one hardware processor that is programmed to:
receive a B-mode ultrasound image of a subject's thyroid;
provide the B-mode ultrasound image to a first trained classification model, wherein the first trained classification model was trained to automatically segment B-mode ultrasound images input to the first trained classification model based on training data comprising manually segmented B-mode ultrasound images;
receive, from the first trained classification model, an output indicating which portions of the B-mode ultrasound image correspond to a nodule;
provide at least a portion of the B-mode ultrasound image corresponding to the nodule to a second trained classification model, wherein the second trained classification model was trained to automatically classify thyroid nodules based on manually labeled portions of B-mode ultrasound image data, color Doppler ultrasound image data, and shear wave elastography ultrasound image data corresponding to benign and malignant nodules; and
receive, from the second trained classification model, an output indicative of a likelihood that the nodule is malignant.
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