Identification of cecum time-location in a colonoscopy video by deep learning analysis of colonoscope movement.

ABSTRACT:

Background

Cecal intubation time is an important component for quality colonoscopy. Cecum is the turning point that determines the insertion and withdrawal phase of the colonoscope. For this reason, obtaining information related with location of the cecum in the endoscopic procedure is very useful. Also, it is necessary to detect the direction of colonoscope's movement and time-location of the cecum.

Methods

In order to analysis the direction of scope's movement, the Horn-Schunck algorithm was used to compute the pixel's motion change between consecutive frames. Horn-Schunk-algorithm applied images were trained and tested through convolutional neural network deep learning methods, and classified to the insertion, withdrawal and stop movements. Based on the scope's movement,

SUBMITTER: Cho M 

PROVIDER: S-EPMC6673422 | biostudies-literature | 2019

REPOSITORIES: biostudies-literature