Given Imaging Ltd.

Eva Niv

Dori Peleg

Dorit Baras

Ryan Sohlden

Iddo Ambor

Orit Elkayam

Eyal Dekel

Avishag Spillinger

Sherry L Fox

Dov Eilot

In accordance with aspects of the present disclosure, a system includes at least one processor and at least one memory storing instructions which, when executed by the processor(s), cause the system to access images of a portion of a gastrointestinal tract (GIT) captured by a capsule endoscopy device; for each of the images, provide, by a deep learning neural network, scores for classifying the image to each of consecutive segments of the GIT; classify each image of a subset of the images, whose scores satisfy a confidence criterion, to one of the consecutive segments of the GIT; refine the classifications of the images in the subset by processing a signal over time corresponding to the classifications of the images in the subset; and estimate, among the images in the subset, a transition () between two adjacent segments of the GIT based on the refined classifications of the images in the subset.

Systems and methods for analyzing a stream of images

Systems and methods may display and/or provide analysis of a number of selected images of a patients gastrointestinal tract collected in-vivo by a swallowable capsule. Images may be displayed for review (e.g., as a study) and/or for further analysis by a user. A subset of images representing the stream of images and automatically selected according to a first selection method may be displayed. On user input, additional images corresponding to a currently displayed image may be displayed, where the additional images are automatically selected according to a second selection method. The second selection method may be based on a relation between images of the stream of in-vivo images and the currently displayed image.

Systems and methods for generating and displaying a study of a stream of in-vivo images

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Hadera, Israel

Eva Niv