Artificial intelligence diagnosis of intrauterine adhesion by 3D ultrasound imaging: a prospective study.

ABSTRACT:

Background

There were a very large number of intrauterine adhesion (IUA) patients. As improving the classification of three-dimensional transvaginal ultrasound (3D-TVUS) of IUA or non-IUA images remains a clinical challenge and is needed to avoid inappropriate surgery. Our study aimed to evaluate deep learning as a method to classify 3D-TVUS of IUA or non-IUA images taken with panoramic technology.

Methods

After meeting an inclusion/exclusion criteria, a total of 4,401 patients were selected for this study. This included 2,803 IUA patients and 1,598 non-IUA patients. IUA was confirmed by hysteroscopy, and each patient underwent one 3D-TVUS examination. Four well-known convolutional neural network (CNN) architectures were selected to classify the IUA images: Visual Geometry G

SUBMITTER: Zhao X 

PROVIDER: S-EPMC10102785 | biostudies-literature | 2023 Apr

REPOSITORIES: biostudies-literature