Abstract: Apparatus and methods are described including a processor (20) configured to receive first and second sets of extraluminal images of a lumen, the second set being acquired while an endoluminal device is being moved through the lumen. The processor designates at least one of the first set of images as a roadmap image, and designates, within the lumen in the roadmap image, a roadmap pathway (42). A plurality of features (44, 46, 48, 50) that are visible within at least some of the second set of extraluminal images are identified, and an arrangement of three or more of the features within the image are compared to a shape of at least a portion of the roadmap pathway. Based upon the comparing, the identified features are mapped to locations along the roadmap pathway within the roadmap image. Other applications are also described.

Abstract: Apparatus and methods are described including, using a computer processor, automatically identifying whether a given pixel within an image corresponds to a portion of an object. A set of concentric circles that are disposed around the pixel are sampled, and a first function is applied to each of the circles such that the circles are defined by a first set of rotationally invariant descriptors. A second function is applied to the set of circles to generate a second set of descriptors, each of which represents a difference between respective pairs of the circles. A third function is applied such that the second set of descriptors becomes rotationally invariant. The processor identifies whether the given pixel corresponds to the portion of the object, based upon the first and second sets of rotationally invariant descriptors. Other applications are also described.

Abstract: Apparatus and methods are described for use with an imaging device (12) configured to acquire a set of angiographic images of a lumen. At least one processor (10) determines blood velocity within the lumen, via image processing. The processor determines a value of a flow-related parameter at the location based upon the determined blood velocity. The processor additionally receives an indication of a value of a second flow-related parameter of the subject, and determines a value of a luminal-flow-related index of the subject at the location, by determining a relationship between the value of the current flow-related parameter and the value of the second flow-related parameter. Other applications are also described.

Abstract: Apparatus and methods are described including, using a computer processor (28), automatically identifying whether a given pixel (111) within an image corresponds to a portion of an object. A set of concentric circles (132a-c) that are disposed around the pixel are sampled, and a first function is applied to each of the circles such that the circles are defined by a first set of rotationally invariant descriptors. A second function is applied to the set of circles to generate a second set of descriptors, each of which represents a difference between respective pairs of the circles. A third function is applied such that the second set of descriptors becomes rotationally invariant. The processor identifies whether the given pixel corresponds to the portion of the object, based upon the first and second sets of rotationally invariant descriptors. Other applications are also described.

Abstract: The invention relates to a method of identifying a biomarker in a tissue sample. The method comprises receiving an acquired image depicting a tissue sample, the pixel intensity values of the acquired image correlating with an autofluorescence signal or of an X-ray induced signal or a signal of a non-biomarker specific stain or a signal of a first biomarker specific stain adapted to selectively stain a first biomarker. The acquired image is input into a trained machine learning logic—MLL which automatically transforms the acquired image into an output image highlighting tissue regions predicted to comprise a second biomarker.

Abstract: An image processing system configured to receive a first fluorescence image generically indicating the presence of biological matter; transform the first image into a transformed first image having a first color; for each of the biomarkers, receive a respective second fluorescence image indicating signals emitted by fluorescence stain selectively staining the biomarker, transforming the second images into a respective transformed second images having a respective second color; overlaying and combining the transformed first and second images; storing and/or displaying the combined image as the simulated digital bright field IHC or ISH image. The first image is created using an autofluorescence reference spectrum of the tissue sample or of a similar tissue sample or by using a fluorescence reference spectrum of a first stain which generically binds to biological matter of the tissue sample for spectrally unmixing of a multi-spectral digital image of the tissue sample.

Abstract: Apparatus and methods are provided for use with an endoluminal data-acquisition device that acquires a set of endoluminal data-points of a lumen of a subject's body at respective locations inside the lumen, a second endoluminal device, and a display configured to display images. At least one processor includes location-association functionality that associates a given data point acquired by the endoluminal data-acquisition device with a given location within the lumen. Location-determination functionality determines, by means of image processing, in an extraluminal image of the second endoluminal device, a current location of at least a portion of the second endoluminal device. Display-driving functionality drives the display to display an indication of the endoluminal data point associated with the location, in response to determining that the portion of the second device is currently at the location. Other applications are also described.

Abstract: An image processing system configured to receive a first fluorescence image generically indicating the presence of biological matter; transform the first image into a transformed first image having a first color; for each of the biomarkers, receive a respective second fluorescence image indicating signals emitted by fluorescence stain selectively staining the biomarker, transforming the second images into a respective transformed second images having a respective second color; overlaying and combining the transformed first and second images; storing and/or displaying the combined image as the simulated digital bright field IHC or ISH image. The first image is created using an autofluorescence reference spectrum of the tissue sample or of a similar tissue sample or by using a fluorescence reference spectrum of a first stain which generically binds to biological matter of the tissue sample for spectrally unmixing of a multi-spectral digital image of the tissue sample.

Abstract: The invention relates to a digital pathology method of generating program logic configured for removing artifacts from digital tissue images. The method comprises generating, for each of a plurality of original images, a first artificially degraded image by applying a first image-artifact-generation logic on each of the original images; and generating the program logic by training an untrained version of a first machine-learning logic that encodes a first artifacts-removal logic on the original images and their respectively generated first degraded images; and returning the trained first machine-learning logic as the program logic or as a component thereof. The first image-artifact-generation logic is A) an image-acquisition-system-specific image-artifact-generation logic or B) a tissue-staining-artifact-generation logic.

Abstract: Apparatus and methods are described for use with an endoluminal data-acquisition device configured to be moved through a lumen of a subject's body, and a two-dimensional angiographic image of the lumen. A value of a luminal-flow-related index of the subject is determined non-invasively at a plurality of locations along the lumen, at least partially by performing image processing on the angiographic image. While the endoluminal data-acquisition device is being moved through the lumen, a set of endoluminal data points of the lumen at a plurality of locations within the lumen is acquired, using the endoluminal data-acquisition device. It is determined that respective endoluminal data points correspond to respective locations along the lumen, and, in response thereto, it is determined that respective endoluminal data points correspond to respective values of the luminal flow-related index. Other applications are also described.

Abstract: Apparatus and methods are provided for use with an endoluminal data-acquisition device that acquires a set of endoluminal data-points of a lumen of a subject's body at respective locations inside the lumen, a second endoluminal device, and a display configured to display images. At least one processor includes location-association functionality that associates a given data point acquired by the endoluminal data-acquisition device with a given location within the lumen. Location-determination functionality determines, by means of image processing, in an extraluminal image of the second endoluminal device, a current location of at least a portion of the second endoluminal device. Display-driving functionality drives the display to display an indication of the endoluminal data point associated with the location, in response to determining that the portion of the second device is currently at the location. Other applications are also described.

Abstract: Apparatus and methods are described including, using a computer processor (28), automatically identifying whether a given pixel (111) within an image corresponds to a portion of an object. A set of concentric circles (132a-c) that are disposed around the pixel are sampled, and a first function is applied to each of the circles such that the circles are defined by a first set of rotationally invariant descriptors. A second function is applied to the set of circles to generate a second set of descriptors, each of which represents a difference between respective pairs of the circles. A third function is applied such that the second set of descriptors becomes rotationally invariant. The processor identifies whether the given pixel corresponds to the portion of the object, based upon the first and second sets of rotationally invariant descriptors. Other applications are also described.

Abstract: The method includes receiving a digital image of a slide, the slide including the tissue sample, a target dot and a fluoro dot. The digital image includes intensity values of the tissue sample, the target dot and the fluoro dot. The method further includes receiving pixel intensities of the fluoro dot depicted in the image; pixel intensities of the target dot depicted in the image; pixel intensities of an area of the tissue sample depicted in the image; fluorescence-inducing molecule density information indicative of the known density of the fluorescence-inducing molecules in the fluoro dot; target molecule density information indicative of the known density of the target molecules in the target dot; and computing the density of target molecules in the area of the tissue sample as a function of the received pixel intensities and the received molecule density information.

Abstract: At least one embodiment relates to an image analysis system for tumor classification. The system is configured for receiving at least one digital image of a tissue sample; analyzing the at least one received image for identifying immune cells and tumor cells in the at least one received image; for each of the identified tumor cells, determining the distance of the tumor cell to the nearest immune cell; computing a proximity measure as a function of the determined distances; in dependence on the proximity measure, classifying the identified tumor cells into tumor cells of an inflammatory tumor or as tumor cells of a non-inflammatory tumor; and storing the classification result on a storage medium and/or displaying the classification result on a display device.

Abstract: Apparatus and methods are described including, while an endoluminal data-acquisition device is being moved through a lumen of a subject, acquiring a plurality of endoluminal data points of the lumen using the endoluminal data-acquisition device. It is determined that, at least one location, no endoluminal data point was acquired. An output is generated using at least a portion of the plurality of endoluminal data points of the lumen acquired using the endoluminal data-acquisition device, the output including an indication that no endoluminal data point was acquired at the location. Other applications are also described.

Abstract: Apparatus and methods are described, including, using an imaging device, acquiring a plurality of images of a portion of a body of a subject. Using a processor, a first feature within each of the images is aligned. At least one enhanced image that is enhanced with respect to the first feature is generated, using the aligned images. Visibility of a second feature is reduced in the enhanced image, and the at least one image that is enhanced with respect to the first feature is displayed upon a display. Other applications are also described.

Abstract: Apparatus and methods are described including, using a computer processor (28), automatically identifying whether a given pixel (111) within an image corresponds to a portion of an object. A set of concentric circles (132a-c) that are disposed around the pixel are sampled, and a first function is applied to each of the circles such that the circles are defined by a first set of rotationally invariant descriptors. A second function is applied to the set of circles to generate a second set of descriptors, each of which represents a difference between respective pairs of the circles. A third function is applied such that the second set of descriptors becomes rotationally invariant. The processor identifies whether the given pixel corresponds to the portion of the object, based upon the first and second sets of rotationally invariant descriptors. Other applications are also described.

Abstract: Apparatus and methods are described including designating within an image of blood vessels of a subject, a target portion of the blood vessels. In response to a first input from a user that designates a single point on the image, a first location within the blood vessels in a vicinity of the designated point is designated. In response to second and third inputs from the user, proximal and distal locations within the target portion are designated. The target portion is designated such that the target portion passes from the proximal location of the target portion to the distal location of the target portion, and such that the target portion includes the first location. Quantitative vessel analysis is performed on the target portion of the blood vessels, and an output is generated based upon the quantitative vessel analysis. Other applications are also described.

Abstract: Apparatus and methods are described for imaging a portion of a body of a subject that undergoes motion. A plurality of image frames of the portion are acquired. A stream of image frames is generated in which a vicinity of a given feature of the image frames is enhanced, by (a) automatically identifying the given feature in each of the image frames, (b) aligning the given feature in two or more of the image frames, (c) averaging sets of two or more of the aligned frames to generate a plurality of averaged image frames, and (d) displaying as a stream of image frames the plurality of averaged image frames. Other embodiments are also described.

Abstract: Apparatus and methods are described including, using a computer processor (28), automatically identifying whether a given pixel (111) within an image corresponds to a portion of an object. A set of concentric circles (132a-c) that are disposed around the pixel are sampled, and a first function is applied to each of the circles such that the circles are defined by a first set of rotationally invariant descriptors. A second function is applied to the set of circles to generate a second set of descriptors, each of which represents a difference between respective pairs of the circles. A third function is applied such that the second set of descriptors becomes rotationally invariant. The processor identifies whether the given pixel corresponds to the portion of the object, based upon the first and second sets of rotationally invariant descriptors. Other applications are also described.