US 2022/0101525 A1Published application

Device and method for producing a digital video classifier

AssigneesAssistance Publique-Hopitaux de Paris, Sorbonne Universite, Centre National De La Recherche Scientifique, éCole Nationale SupéRieure De L'éLectronique Et De Ses Applications, Cy Cergy Paris Université

InventorsMarc Souchaud, Aymeric Histace, Romain Leenhardt, Xavier Dray

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Abstract

The present invention concerns a device for producing a “digital video classifier” configured to determine the quality of cleanliness of one or more segments of the digestive tube in a video capsule endoscopy (VCE) of a subject, comprising: a VCE allowing the acquisition of videos of segments of the digestive tube, video storage means, coupled with the VCE, an “image database” with images extracted from VCE exams, a “video database” with videos extracted from VCE exams, calculating means connected to the video storage means, and to the databases, and configured for performing a statistical learning for the generation of a “digital image classifier” from the “image database” and which classifies the images in adequate cleanliness or non-adequate cleanliness; generating the “digital video classifier” capable of classifying a video of a subject as being of adequate cleanliness or of non-adequate cleanliness of one or more segments of the digestive tube.

Claims17

Dependent claims

A device for producing a digital video classifier configured to determine a quality of cleanliness of one or more segments of a digestive tube of a subject from a capsule endoscopy video of the subject digestive tube, comprising:

a data storage medium configured to store:
an image database with images extracted from video capsule endoscopy—VCE—exams and categorized into predetermined images categories including images with adequate cleanliness and images with non-adequate cleanliness;
said predetermined image categories referring to a score determined by a visual analysis of the images based on at least one medical criterion, and
a video database with videos extracted from VCE exams categorized into predetermined video categories including videos with adequate cleanliness and videos with non-adequate cleanliness;
said predetermined video categories referring to a score determined by a visual analysis of the videos, based on at least one medical criterion,
the at least one medical criterion being selected from:
percentage of mucosa visualized, luminosity, presence of bubbles, presence of bile/chyme, presence of liquids and/or undigested debris,
one or several processors connected to the data storage medium, and configured for:
(A) performing a statistical learning for generation of a digital image classifier from the image database and which classifies the images in adequate cleanliness or non-adequate cleanliness;
(B) generating the digital video classifier, by the following steps:
a) extraction of all the successive images of each video from the video database;
b) automatic classification of the quality of all the successive images from each extracted video, in adequate cleanliness or non-adequate cleanliness, by the digital image classifier, and computing a video cleanliness score for each video according to a proportion of images whose quality is of adequate cleanliness;
c) automatic classifications of the videos into videos with adequate cleanliness and videos with non-adequate cleanliness, each of said classifications of the videos being done with one of a plurality of threshold values applied to the video cleanliness score;
d) computing a plurality of receiver operating characteristics—ROC—for each of the automatic classifications of the videos according to the predetermined video categories;
e) computing of a desired threshold value between 0% and 100% of the video cleanliness score allowing to obtain desired values in terms of ROC performance,
the value of this desired threshold of the video cleanliness score becoming, in combination with the digital image classifier, the digital video classifier capable of classifying a video of one or more segments of a subject digestive tube as being of adequate cleanliness or of non-adequate cleanliness.

13 more elements

A method for producing a digital video classifier configured to determine a quality of cleanliness of one or more segments of a digestive tube of a subject from a capsule endoscopy video of the subject digestive tube, said method being executed by one or several processors connected to a data storage medium configured to store:

an image database with images extracted from video capsule endoscopy—VCE—exams and categorized into predetermined images categories including images with adequate cleanliness and images with non-adequate cleanliness;
said predetermined image categories referring to a score determined by a visual analysis of the images based on at least one medical criterion, and
a video database with videos extracted from VCE exams categorized into predetermined video categories including videos with adequate cleanliness and videos with non-adequate cleanliness;
said predetermined video categories referring to a score determined by a visual analysis of the videos, based on at least one medical criterion,
the at least one medical criterion being selected from:
percentage of mucosa visualized, luminosity, presence of bubbles, presence of bile/chyme, presence of liquids and/or undigested debris,
said method comprising the following steps:
(A) performing a statistical learning for the generation of a “digital image classifier” from the “image database” and which classifies the images in adequate cleanliness or non-adequate cleanliness;
(B) generating the digital video classifier, by the following steps:
a) extraction of all the successive images of each video from the video database;
b) automatic classification of the quality of all the successive images from each extracted video, in adequate cleanliness or non-adequate cleanliness, by the digital image classifier, and computing a video cleanliness score for each video according to a proportion of images whose quality is of adequate cleanliness;
c) automatic classifications of the videos into video with adequate cleanliness and videos with non-adequate cleanliness, each of said classifications of the videos being done with one of a plurality of threshold values applied to the video cleanliness score;
d) computing a plurality of receiver operating characteristic—ROC—for each of the automatic classifications of the videos according to the predetermined video categories;
e) computing of a desired threshold value between 0% and 100% of the video cleanliness score allowing to obtain desired values in terms of ROC performance,
the value of this desired threshold of the video cleanliness score becoming, in combination with the digital image classifier, the digital video classifier capable of classifying a video of one or more segments of a subject digestive tube as being of adequate cleanliness or of non-adequate cleanliness.

12 more elements

Dependencies are inferred from the claim text.