Abstract: A system and method for segmenting an image stream to a plurality of segments is provided. A processing unit may be configured to calculate a set of pixel-based properties for frames of an image stream, and detect segments of constant mean values in the sets of pixel-based properties. The segments of constant mean values are detected by using a window method that determines possible partition points of the window, and calculating a difference between mean values of the sets of pixel-based properties for each sub-window of frames. Points of change may be identified in the calculated difference between mean values of the sets of pixel-based properties. A display unit may display a summarized representation of the image stream, wherein the summarized representation includes a plurality of segments, each segment corresponding to a segment of constant mean values in the sets of pixel-based properties.

Abstract: A system and method for segmenting an image stream to a plurality of segments is provided. A processing unit may be configured to calculate a set of pixel-based properties for frames of an image stream, and detect segments of constant mean values in the sets of pixel-based properties. The segments of constant mean values are detected by using a window method that determines possible partition points of the window, and calculating a difference between mean values of the sets of pixel-based properties for each sub-window of frames. Points of change may be identified in the calculated difference between mean values of the sets of pixel-based properties. A display unit may display a summarized representation of the image stream, wherein the summarized representation includes a plurality of segments, each segment corresponding to a segment of constant mean values in the sets of pixel-based properties.

Abstract: A system and method may analyse and display intestinal motility events, based on an image stream captured by an in vivo imaging device. According to some embodiments, the system includes a storage unit to store image frames from the image stream, a processor to select a strip of pixels from a plurality of image frames of the image stream and to align the selected strips adjacently to form a motility events bar, and a visual display unit for displaying the motility events bar to a user.

Abstract: A method and system cascade analysis for intestinal contraction detection is provided by extracting from image frames captured in-vivo. The method and system also relate to the detection of turbid liquids in intestinal tracts, to automatic detection of video image frames taken in the gastrointestinal tract including a field of view obstructed by turbid media, and more particularly to extraction of image data obstructed by turbid media.

Abstract: A system and method may analyse and display intestinal motility events, based on an image stream captured by an in vivo imaging device. According to some embodiments, the system includes a storage unit to store image frames from the image stream, a processor to select a strip of pixels from a plurality of image frames of the image stream and to align the selected strips adjacently to form a motility events bar, and a visual display unit for displaying the motility events bar to a user.

Abstract: A method and system for determining intestinal dysfunction condition are provided by classifying and analyzing image frames captured in-vivo. The method and system also relate to the detection of contractile activity in intestinal tracts, to automatic detection of video image frames taken in the gastrointestinal tract including contractile activity, and more particularly to measurement and analysis of contractile activity of the GI tract based on image intensity of in vivo image data.

Abstract: A system and method for comparing captured sequences of in-vivo images with (e.g., template or model) sequences, for example, for computer-automated recognition of contractions. The size of the opening of an in-vivo lumen passageway represented in each frame in a subset of frames of an image stream captured in vivo may be measured. Frames in the subset of frames of the image stream having a local minimum size of the lumen passageway may be identified. The subset of frames may be divided into segments of sequential frames at frames having local maximum lumen sizes before and after the identified frame having a local minimum size of the lumen passageway to generate contraction sequences. A plurality of the contraction sequences may be compared to template sequences. A plurality of the contraction sequences may be displayed.

Abstract: A device, system and method for automatic detection of contractile activity of a body lumen in an image frame is provided, wherein image frames during contractile activity are captured and/or image frames including contractile activity are automatically detected, such as through pattern recognition and/or feature extraction to trace image frames including contractions, e.g., with wrinkle patterns. A manual procedure of annotation of contractions, e.g. tonic contractions in capsule endoscopy, may consist of the visualization of the whole video by a specialist, and the labeling of the contraction frames. Embodiments of the present invention may be suitable for implementation in an in vivo imaging system.

Abstract: A method and system cascade analysis for intestinal contraction detection is provided by extracting from image frames captured in-vivo. The method and system also relate to the detection of turbid liquids in intestinal tracts, to automatic detection of video image frames taken in the gastrointestinal tract including a field of view obstructed by turbid media, and more particularly to extraction of image data obstructed by turbid media.

Abstract: A method and system for detection of intestinal contraction may include detecting an obstructed portion of an image frame captured in-vivo. The obstructed portion of the image frame may include an area within an image frame that is obstructed by turbid intestinal content. The method and system may set a threshold for the area of the obstructed portion in the image frame, to determine an invalid frame and may remove the invalid frame from an image stream.

Abstract: A system and method for comparing captured sequences of in-vivo images with (e.g., template) sequences, for example, for computer-automated diagnosis. Captured in vivo images may be divided into a plurality of captured image sequences. For each of the plurality of captured sequences, the processor may assign a first and second set of scores to each frame in the captured sequence and align each frame in the captured sequence with one or more frames in the template sequence for which the comparisons therebetween generate the minimum scores in the first and second sets of scores. The processor may define a match between the template sequence and captured sequences having a combination of scores in the first and second sets of scores for the frames in the captured sets compared with the one or more aligned frames in the template sequence, which are below or above a threshold value.

Abstract: A device, system and method for automatic detection of contractile activity of a body lumen in an image frame is provided, wherein image frames during contractile activity are captured and/or image frames including contractile activity are automatically detected, such as through pattern recognition and/or feature extraction to trace image frames including contractions, e.g., with wrinkle patterns. A manual procedure of annotation of contractions, e.g. tonic contractions in capsule endoscopy, may consist of the visualization of the whole video by a specialist, and the labeling of the contraction frames. Embodiments of the present invention may be suitable for implementation in an in vivo imaging system.

Abstract: A method and system for determining intestinal dysfunction condition are provided by classifying and analyzing image frames captured in-vivo. The method and system also relate to the detection of contractile activity in intestinal tracts, to automatic detection of video image frames taken in the gastrointestinal tract including contractile activity, and more particularly to measurement and analysis of contractile activity of the GI tract based on image intensity of in vivo image data.

Abstract: A system and method for comparing captured sequences of in-vivo images with (e.g., template or model) sequences, for example, for computer-automated recognition of contractions. The size of the opening of an in-vivo lumen passageway represented in each frame in a subset of frames of an image stream captured in vivo may be measured. Frames in the subset of frames of the image stream having a local minimum size of the lumen passageway may be identified. The subset of frames may be divided into segments of sequential frames at frames having local maximum lumen sizes before and after the identified frame having a local minimum size of the lumen passageway to generate contraction sequences. A plurality of the contraction sequences may be compared to template sequences. A plurality of the contraction sequences may be displayed.

Abstract: A system and method for comparing captured sequences of in-vivo images with (e.g., template) sequences, for example, for computer-automated diagnosis. Captured in vivo images may be divided into a plurality of captured image sequences. For each of the plurality of captured sequences, the processor may assign a first and second set of scores to each frame in the captured sequence and align each frame in the captured sequence with one or more frames in the template sequence for which the comparisons therebetween generate the minimum scores in the first and second sets of scores. The processor may define a match between the template sequence and captured sequences having a combination of scores in the first and second sets of scores for the frames in the captured sets compared with the one or more aligned frames in the template sequence, which are below or above a threshold value.

Abstract: A device, system and method for automatic detection of contractile activity of a body lumen in an image frame is provided, wherein image frames during contractile activity are captured and/or image frames including contractile activity are automatically detected, such as through pattern recognition and/or feature extraction to trace image frames including contractions, e.g., with wrinkle patterns. A manual procedure of annotation of contractions, e.g. tonic contractions in capsule endoscopy, may consist of the visualization of the whole video by a specialist, and the labeling of the contraction frames. Embodiments of the present invention may be suitable for implementation in an in vivo imaging system.

Abstract: A method for automatically detecting a post-duodenal boundary in an image stream of the gastrointestinal (GI) tract. The image stream is sampled to obtain a reduced set of images for processing. The reduced set of images is filtered to remove non-valid frames or non-valid portions of frames, thereby generating a filtered set of valid images. A polar representation of the valid images is generated. Textural features of the polar representation are processed to detect the post-duodenal boundary of the GI tract.

Abstract: A method and system cascade analysis for intestinal contraction detection is provided by extracting from image frames captured in-vivo. The method and system also relate to the detection of turbid liquids in intestinal tracts, to automatic detection of video image frames taken in the gastrointestinal tract including a field of view obstructed by turbid media, and more particularly to extraction of image data obstructed by turbid media.

Abstract: A method and system for determining intestinal dysfunction condition are provided by classifying and analyzing image frames captured in-vivo. The method and system also relate to the detection of contractile activity in intestinal tracts, to automatic detection of video image frames taken in the gastrointestinal tract including contractile activity, and more particularly to measurement and analysis of contractile activity of the GI tract based on image intensity of in vivo image data.