Application of Artificial Intelligence For Real-Time Anatomical Recognition During Endoscopic Ultrasound Evaluation: A Pilot Study

Abstract:

Aims We aimed to develop an artificial intelligence model that recognizes in real-time the anatomical structures during EUS evaluations. Methods A single-center, pilot study. We developed two convolutional neuronal networks from linear and radial endoscopic ultrasound videos from patients without pathologies. The AI models were developed using an automated machine learning software (AI Works, MD Consulting group, Ecuador). Two expert endosonographers trained the two independent models. The linear and radial EUS algorithms metrics were calculated for recognizing anatomical structures during EUS evaluations. Results We included eight anatomical structures from twelve endoscopic ultrasound videos for the development of the EUS-AI algorithms. A total of 8113 samples were captured from the EUS videos (6354 for radial and 1759 for linear). The anatomical structures were recognized and labeled for …

Año de publicación:

2021

Keywords:

Fuente:

google