Method and system for identification of red colored pathologies in vivo
First Claim
1. A method for identification of red pathologies in in-vivo images, the method comprising:
- receiving an image captured in-vivo;
identifying candidate pathology regions in the image by identifying red regions in the image;
identifying one or more features indicative of the probability of pathology in said candidate regions by applying on the image a set of analyses, each analysis for identifying a feature indicative of the probability of pathology, wherein said set of analyses comprises at least one analysis for identifying a physical feature causing false identification of apparent red regions in the image, and identification of said feature in positional relation to a candidate region in the image is indicative of low probability of pathology depicted by said candidate, wherein said physical feature is a bubble, and said at least one analysis comprises identifying whiteness features in the perimeter of a candidate region; and
calculating an image score for said image based on said one or more identified features, said image score indicative of existence in the image of at least one candidate region with high probability of pathology, wherein calculating an image score comprises calculating a candidate score for at least one identified candidate region based on said features, said candidate score indicative of the probability of pathology being imaged in said candidate region, wherein said image score corresponds to the candidate score of the candidate region with the highest probability of pathology in the image.
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Abstract
A system and method may identify pathologies such as red pathologies in in-vivo images. Candidate pathology regions may be identified by identifying red regions. Features indicative of the probability of pathology in candidate regions may be identified. An image score for an image may be identified based on one or more identified features, the image score indicative of existence in the image of at least one candidate region with high probability of pathology. Calculating an image score may include calculating a candidate score for at least one identified candidate region based on features, the candidate score indicative of the probability of pathology being imaged in said candidate region, where the image score corresponds to the candidate score of the candidate region with the highest probability of pathology in the image.
126 Citations
21 Claims
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1. A method for identification of red pathologies in in-vivo images, the method comprising:
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receiving an image captured in-vivo; identifying candidate pathology regions in the image by identifying red regions in the image; identifying one or more features indicative of the probability of pathology in said candidate regions by applying on the image a set of analyses, each analysis for identifying a feature indicative of the probability of pathology, wherein said set of analyses comprises at least one analysis for identifying a physical feature causing false identification of apparent red regions in the image, and identification of said feature in positional relation to a candidate region in the image is indicative of low probability of pathology depicted by said candidate, wherein said physical feature is a bubble, and said at least one analysis comprises identifying whiteness features in the perimeter of a candidate region; and calculating an image score for said image based on said one or more identified features, said image score indicative of existence in the image of at least one candidate region with high probability of pathology, wherein calculating an image score comprises calculating a candidate score for at least one identified candidate region based on said features, said candidate score indicative of the probability of pathology being imaged in said candidate region, wherein said image score corresponds to the candidate score of the candidate region with the highest probability of pathology in the image. - View Dependent Claims (2, 3, 4, 5, 6, 7, 10, 11, 19)
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8. A method for identification of red pathologies in in-vivo images, the method comprising:
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receiving an image captured in-vivo; identifying candidate pathology regions in the image by identifying red regions in the image; identifying one or more features indicative of the probability of pathology in said candidate regions by applying on the image a set of analyses, each analysis for identifying a feature indicative of the probability of pathology, wherein identifying one or more features comprises calculating a distance score for at least a first candidate region by estimating a distance between the first candidate region and at least one additional candidate region in the image; and calculating an image score for said image based on said one or more identified features, said image score indicative of existence in the image of at least one candidate region with high probability of pathology, wherein calculating an image score comprises calculating a candidate score for at least one identified candidate region based on said features, said candidate score indicative of the probability of pathology being imaged in said candidate region, wherein said image score corresponds to the candidate score of the candidate region with the highest probability of pathology in the image.
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9. A method for identification of red pathologies in in-vivo images, the method comprising:
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receiving an image captured in-vivo; identifying candidate pathology regions in the image by identifying red regions in the image; identifying one or more features indicative of the probability of pathology in said candidate regions by applying on the image a set of analyses, each analysis for identifying a feature indicative of the probability of pathology, wherein said set of analyses comprises at least one analysis for identifying a physical feature causing false identification of apparent red regions in the image, and identification of said feature in positional relation to a candidate region in the image is indicative of low probability of pathology depicted by said candidate, wherein said physical feature is a fold in an in vivo tissue, and wherein said at least one analysis comprises identifying correlation of color saturation distribution within the candidate region; and calculating an image score for said image based on said one or more identified features, said image score indicative of existence in the image of at least one candidate region with high probability of pathology, wherein calculating an image score comprises calculating a candidate score for at least one identified candidate region based on said features, said candidate score indicative of the probability of pathology being imaged in said candidate region, wherein said image score corresponds to the candidate score of the candidate region with the highest probability of pathology in the image. - View Dependent Claims (18)
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12. A system for identification of red pathologies in in vivo images, the system comprising:
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a memory storing in-vivo images; and a processor to; identify candidate pathology regions by identifying red regions in an image captured in vivo; identify one or more features indicative of the probability of pathology in said candidate regions by applying on the image a set of analyses, each analysis for identifying a feature indicative of the probability of pathology, wherein identifying one or more features comprises calculating a distance score for at least a first candidate region by estimating a distance between the first candidate region and at least one additional candidate region in the image; calculate a candidate score for one or more identified candidate region based on said features, said candidate score indicative of the probability of pathology being imaged in said candidate region; and calculate an image score for said image based on said one or more identified features, said image score indicative of existence in the image of at least one candidate region with high probability of pathology, wherein said image score corresponds to the candidate score of the candidate region with the highest probability of pathology in the image. - View Dependent Claims (13, 14, 15, 16, 17)
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20. A system for identification of red pathologies in in vivo images, the system comprising:
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a memory storing in-vivo images; and a processor to; receive an image captured in-vivo; identify candidate pathology regions in the image by identifying red regions in the image; identify one or more features indicative of the probability of pathology in said candidate regions by applying on the image a set of analyses, each analysis for identifying a feature indicative of the probability of pathology, wherein said set of analyses comprises at least one analysis for identifying a physical feature causing false identification of apparent red regions in the image, and identification of said feature in positional relation to a candidate region in the image is indicative of low probability of pathology depicted by said candidate, wherein said physical feature is a bubble, and said at least one analysis comprises identifying whiteness features in the perimeter of a candidate region; and calculate an image score for said image based on said one or more identified features, said image score indicative of existence in the image of at least one candidate region with high probability of pathology, wherein calculating an image score comprises calculating a candidate score for at least one identified candidate region based on said features, said candidate score indicative of the probability of pathology being imaged in said candidate region, wherein said image score corresponds to the candidate score of the candidate region with the highest probability of pathology in the image.
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21. A system for identification of red pathologies in in vivo images, the system comprising:
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a memory storing in-vivo images; and a processor to; receive an image captured in-vivo; identify candidate pathology regions in the image by identifying red regions in the image; identify one or more features indicative of the probability of pathology in said candidate regions by applying on the image a set of analyses, each analysis for identifying a feature indicative of the probability of pathology, wherein said set of analyses comprises at least one analysis for identifying a physical feature causing false identification of apparent red regions in the image, and identification of said feature in positional relation to a candidate region in the image is indicative of low probability of pathology depicted by said candidate, wherein said physical feature is a fold in an in vivo tissue, and wherein said at least one analysis comprises identifying correlation of color saturation distribution within the candidate region; and calculating an image score for said image based on said one or more identified features, said image score indicative of existence in the image of at least one candidate region with high probability of pathology, wherein calculating an image score comprises calculating a candidate score for at least one identified candidate region based on said features, said candidate score indicative of the probability of pathology being imaged in said candidate region, wherein said image score corresponds to the candidate score of the candidate region with the highest probability of pathology in the image.
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Specification