Tel Hashomer Medical Research Infrastructure and Services Ltd.

Imedis Ai Ltd

Shmuel Yitzhak Pfeffer

Arnaldo Mayer

Miriam Sklair-Levy

Tomer Glottmann

Aviel Blumenfeld

A method of processing a given region of interest (ROI) of an X-ray image of a person's breast to determine presence of a malignancy, the X-ray image having X-ray pixels that indicate intensity of X-rays that passed through the breast to generate the image, the method comprising: for each given X-ray pixel in the given ROI and each of a selection of J(r) X-ray pixels at respective pixel radii PR(r), 1&#x2264;r&#x2264;R, from the given x-ray pixel, determining a binary number that provides a measure X-ray intensity indicated by the selected X-ray pixel relative to X-ray intensity indicated by the given X-ray pixel; using the determined binary numbers for the selected X-ray pixels at each pixel radius PR(r) to determine a decimal number for the pixel radius PR(r); histogramming the frequency of occurrence of values of the determined decimal numbers as a function of pixel radius for the given X-ray pixels in the given ROI; determining a texture feature vector, for the given ROI having components that are equal to the frequencies of occurrence for a selection of M histogrammed values; and processing the histogrammed frequencies of occurrence for the M values to determine whether the given ROI is malignant.

Mammography apparatus

Apparatus for diagnosing breast cancer, the apparatus comprising a controller having a set of instructions executable to: acquire a contrast enhanced region of interest (CE-ROI) in an X-ray image of a patient's breast, the X-ray image comprising X-ray pixels that indicate intensity of X-rays that passed through the breast to generate the image; determine a texture neighborhood for each of a plurality of X-ray pixels in the CE-ROI, the texture neighborhood for a given X-ray pixel of the plurality of X-ray pixels extending to a bounding pixel radius of BPR pixels from the given pixel; generate a texture feature vector (TF) having components based on the indications of intensity provided by a plurality of X-ray pixels in the CE-ROI that are located within the texture neighborhood; and use a classifier to classify the texture feature vector TF to determine whether the CE-ROI is malignant.

Systems and methods for the improved analysis and generation of medical imaging reports are disclosed. In particular, the present disclosure provides systems and methods that may be used for the automated analysis of radiological information, such as medical images and related text statements for discrepancy analysis, accuracy analysis and quality assurance. Systems and methods may include receiving medical images and textual data, generating enhanced medical image data by applying an artificial intelligence module to the received medical images, generating structured text data by applying a natural language processing module to the received textual data, and generating improved medical image reports and/or alerts based on the generated enhanced medical image data and the generated structured text data.

Systems and methods for improved analysis and generation of medical imaging reports

A method of diagnosing breast cancer, the method comprising: acquiring a contrast enhanced region of interest (CE-ROI) comprised in an X-ray image of a patient's breast, the X-ray image comprising X-ray pixels that indicate intensity of X-rays that passed through the breast to generate the image; generating a texture feature vector (TF) having components based on the indications of intensity provided by a plurality of X-ray pixels in the CE-ROI; and using a classifier to classify the texture feature vector TF to determine whether the CE-ROI is malignant.

Growing community of inventors

Lod, Israel

Shmuel Yitzhak Pfeffer