Deep learning to diagnose pouch of Douglas obliteration with ultrasound sliding sign.

ABSTRACT:

Objectives

Pouch of Douglas (POD) obliteration is a severe consequence of inflammation in the pelvis, often seen in patients with endometriosis. The sliding sign is a dynamic transvaginal ultrasound (TVS) test that can diagnose POD obliteration. We aimed to develop a deep learning (DL) model to automatically classify the state of the POD using recorded videos depicting the sliding sign test.

Methods

Two expert sonologists performed, interpreted, and recorded videos of consecutive patients from September 2018 to April 2020. The sliding sign was classified as positive (i.e. normal) or negative (i.e. abnormal; POD obliteration). A DL model based on a temporal residual network was prospectively trained with a dataset of TVS videos. The model was tested on an independent test set

SUBMITTER: Maicas G 

PROVIDER: S-EPMC8801033 | biostudies-literature | 2021 Dec

REPOSITORIES: biostudies-literature