Parathyroid gland identification and angiography classification using simple machine learning methods.
Journal:
BJS open
PMID:
39468722
Abstract
BACKGROUND: Near-infrared indocyanine green angiography allows experienced surgeons to reliably evaluate parathyroid gland vitality during thyroid and parathyroid operations in order to predict postoperative function. To facilitate equal performance between surgeons, we developed an automatic computational quantification method using computer vision that portrays expert interpretation of visualized parathyroid gland near-infrared indocyanine green angiographic fluorescence signals.