US 11,937,973 B2
Systems and media for automatically diagnosing thyroid nodules
Zeynettin Akkus, Rochester, MN (US); Bradley J. Erickson, Rochester, MN (US); and Matthew R. Callstrom, Rochester, MN (US)
Assigned to Mayo Foundation for Medical Education and Research, Rochester, MN (US)
Appl. No. 17/058,871
Filed by Mayo Foundation for Medical Education and Research, Rochester, MN (US)
PCT Filed May 31, 2019, PCT No. PCT/US2019/034870
§ 371(c)(1), (2) Date Nov. 25, 2020,
PCT Pub. No. WO2019/232346, PCT Pub. Date Dec. 5, 2019.
Claims priority of provisional application 62/678,736, filed on May 31, 2018.
Prior Publication US 2021/0219944 A1, Jul. 22, 2021
Int. Cl. A61B 8/08 (2006.01); G06N 3/045 (2023.01); G06N 3/084 (2023.01)
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
OG exemplary drawing
 
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.