Abstract: This specification describes systems and methods for obtaining various patient related data for inflammatory bowel disease (IBD). The methods and systems are configured for using machine learning to determine measurements of various characteristics and provide analysis related to IBD. The methods and systems may also obtain and incorporate electronic health data as well as other relevant data of patients along with endoscopic data to use for prediction IDB progression and recommending treatment.

Abstract: This specification describes systems and methods for performing endoscopy, obtaining medical images for inflammatory bowel disease (IBD) and scoring severity of IBD in patients. The methods and systems are configured for using machine learning to determine measurements of various characteristics related to IBD. The methods and systems may also obtain and incorporate electronic health data of patients along with endoscopic data to use for scoring purposes.

Abstract: Disclosed is the automated rapid advancement of a guide wire through a guide catheter using x-ray markers. The procedure involves providing a guide wire with a marker at or adjacent its tip, providing a guide catheter with a marker at or adjacent its distal terminus, rapidly advancing the guide wire through the guide catheter from its proximal end to its distal end under the control of an automated apparatus, and terminating the automated rapid advancement when the guide wire tip marker becomes adjacent to the guide catheter distal end marker. Fluoroscopic images may be taken of the of the guide wire as it rapidly advances through the guide catheter and image processing software used to determine when to terminate the rapid advancement. This software may use either the position or the velocity of the guide wire to make this determination.

Abstract: Disclosed is the automated rapid advancement of a guide wire through a guide catheter using x-ray markers. The procedure involves providing a guide wire with a marker at or adjacent its tip, providing a guide catheter with a marker at or adjacent its distal terminus, rapidly advancing the guide wire through the guide catheter from its proximal end to its distal end under the control of an automated apparatus, and terminating the automated rapid advancement when the guide wire tip marker becomes adjacent to the guide catheter distal end marker. Fluoroscopic images may be taken of the of the guide wire as it rapidly advances through the guide catheter and image processing software used to determine when to terminate the rapid advancement. This software may use either the position or the velocity of the guide wire to make this determination.

Abstract: The present disclosure involves a process for guiding the distal end of a guide wire or working catheter as it emerges from the distal end of a guide catheter into a blood vessel. The distal end of the guide wire or working catheter is provided with an X-ray marker, a determination is made that this distal end has emerged from the distal end of the guide catheter and a fluoroscopic image of the distal end of a guide wire or working catheter is taken. This image is correlated with the length of guide wire or working catheter inserted into the guide catheter. After further advancement of the guide wire or working catheter, another fluoroscopic image of the distal end of a guide wire or working catheter is taken and this image is correlated with the length of guide wire or working catheter which has been inserted into the guide catheter.

Abstract: This disclosure involves the use of X-ray markers that appear in fluoroscopic images and are detected by image processing software to partially or fully automate or assist in the performance of one or more of the steps of a percutaneous interventional procedure typically involving a catheter device.

Abstract: The invention provides methods for determining the probability that a given region of a tissue sample contains tissue of a given category, such as CIN 1 (cervical intraepithelial neoplasia, grade 1), CIN 2/3 (cervical intraepithelial neoplasia grades 2 and/or 3), normal squamous, normal columnar, and metaplasia, for example. The invention provides increased diagnostic accuracy by combining a plurality of statistical classification techniques. Furthermore, in one embodiment, the invention comprises combining one or more statistical techniques with one or more non-statistical classification techniques.

Abstract: The invention provides methods for displaying diagnostic results obtained from a tissue sample. In general, the invention assigns tissue-class probability values to discrete regions of a patient sample, and creates an overlay for displaying the results. The overlay facilitates display of the tissue class probabilities in a way that reflects the diagnostic relevance of the data. For example, methods of the invention comprise applying filtering and color-blending techniques in order to facilitate display of diagnostic results.

Abstract: The invention provides systems for automatically localizing areas of disease within a tissue sample using fluorescence spectra, reflectance spectra, and video images obtained from the sample. The invention further provides systems for displaying, marking, and treating the identified areas so that healthy surrounding tissue suffers minimal impact upon treatment and/or excision of the diseased tissue. The invention facilitates minimally-invasive treatment by accurately directing treatment to only those areas that are identified as diseased.

Abstract: The invention provides methods for determining the probability that a given region of a tissue sample contains tissue of a given category, such as CIN 1 (cervical intraepithelial neoplasia, grade 1), CIN 2/3 (cervical intraepithelial neoplasia grades 2 and/or 3), normal squamous, normal columnar, and metaplasia, for example. The invention provides increased diagnostic accuracy by combining a plurality of statistical classification techniques. Furthermore, in one embodiment, the invention comprises combining one or more statistical techniques with one or more non-statistical classification techniques.

Abstract: The invention provides methods for displaying diagnostic results obtained from a tissue sample. In general, the invention assigns tissue-class probability values to discrete regions of a patient sample, and creates an overlay for displaying the results. The overlay facilitates display of the tissue class probabilities in a way that reflects the diagnostic relevance of the data. For example, methods of the invention comprise applying filtering and color-blending techniques in order to facilitate display of diagnostic results.

Abstract: The invention provides methods for processing tissue-derived optical data for use in a classification algorithm. Methods of the invention comprise application of image masks for automatically identifying ambiguous or unclassifiable optical data. The optical data may comprise, for example, spectral data and/or acetowhitening kinetic data used in a tissue classification scheme. The invention improves the accuracy of tissue classification, in part, by properly identifying and accounting for image data from tissue regions that are affected by an obstruction and/or regions that lie outside a diagnostic zone of interest.

Abstract: A technique for temporal smoothing of results from a scene analysis process which creates a sequence of visually pleasing and acceptable images generated in whole or part from such results. The technique applies temporal smoothing across time-related sets of scene analysis results. The spatial smoothing can be applied at various steps in the process: to images in the original sequence, to intermediate or final results of scene analysis in either a pixel-oriented or geometric domain, or to the images generated in whole or part from the scene analysis results. In a preferred embodiment, different levels of smoothing are applied to different parts of the intermediate or final results. The differentiation can be done using image masks (for pixel-oriented results) or geometry selection techniques (for geometric results).

Abstract: A technique for displaying a visual representation of an estimated three-dimensional scene structure and the values of various parameters associated with the scene, together with a visual representation of at least one two-dimensional image used in the scene structure estimation algorithm. A user inputs information by adjusting parameters and/or specifying an element or region of the visual representations and supplies mark-ups and other information such as attributes for the element or region to be applied during a next iteration of the scene structure estimation algorithm. The scene structure estimation algorithm is then re-executed and the process repeats until the user is satisfied with the resulting visual scene structure.

Abstract: A technique for converging upon a computer-based model of a real world or synthetic scene. The computer model makes use of abstraction-based data objects as well as image-based data objects. A correlation mesh provides links between related image-based and abstraction-based objects. An initial step in a process analyzes an input image stream and user inputs to derive initial image-based objects and abstraction-based objects for the scene model. Subsequent steps in the process allow user inputs to refine the image-based objects, abstraction-based objects and/or the correlation mesh. As a result, refinements to the image-based object model of the scene can improve the abstraction-based model of the scene, and refinements to the abstraction-based object model can improve the image-based model.

Abstract: A method for Golden Template Comparison (GTC) is provided that can be used to efficiently perform flaw and defect detection on a two-dimensional test image that is at least rotated and/or scaled and/or sub-pixel translated. Run-time inspection speed and accuracy is substantially improved by retreiving a golden template image that is rotated and/or scaled and/or translated in a manner substantially similar to the test image. This is accomplished by storing, in an array, a varied plurality of golden template images, each golden template image being characterized by a different combination of at least rotation and/or scale and/or sub-pixel translation. The array is indexed by the respective quantized rotation and/or quantized scale and/or sub-pixel translation of each version of the golden template image. The array can be either one-dimensional or multi-dimensional.

Abstract: A very fast, memory efficient, single-step solution for coarse alignment with determination of angular displacement, and inspection for surface defects on circular objects with non-symmetric patterns and random orientation is described. A suitable geometric partition model of an image is constructed that includes a plurality of spatial bins that can be used for rotation estimation and defect detection. In one embodiment for inspection of circular objects, the geometric partitioning includes 256 spatial bins constituted by concentric circular rings divided into sectors. The number of sectors and thickness of the rings are such that the approximate number of pixels in each region is the same.

Abstract: A coprocessor in an image processing system is coupled to the bus to which a CPU and RAM holding image data are also coupled. The coprocessor extracts an input pixel stream corresponding to input images from selected bus transactions, performs computations on the input stream to produce output pixel streams corresponding to output images, and inserts the output pixel streams into selected CPU-to-memory bus transactions so that the memory stores the data. The CPU generates the selected bus transactions with specially marked address and/or control signals. The coprocessor includes a lookup table, and a first row delay. The row delay accumulates the three most recent rows of input pixels, which are sent to Sobel and rank processing sections for neighborhood processing. The results are thresholded and formatted, and are either output directly or passed through an additional pair of row delays to accumulate three rows of result data for neighborhood peak detection.

Abstract: A coprocessor in an image processing system is coupled to the bus to which a CPU and RAM holding image data are also coupled. The coprocessor extracts an input pixel stream corresponding to input images from selected bus transactions, performs computations on the input stream to produce output pixel streams corresponding to output images, and inserts the output pixel streams into selected CPU-to-memory bus transactions so that the memory stores the data. The CPU generates the selected bus transactions with specially marked address and/or control signals. The coprocessor includes a lookup table, and a first row delay. The row delay accumulates the three most recent rows of input pixels, which are sent to Sobel and rank processing sections for neighborhood processing. The results are thresholded and formatted, and are either output directly or passed through an additional pair of row delays to accumulate three rows of result data for neighborhood peak detection.