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 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 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 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 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 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.