Tel Hashomer Medical Research Infrastructure and Services Ltd.

Tel Aviv University

Miriam Sklair-Levy

Arnaldo Mayer

Shmuel Yitzhak Pfeffer

Hedva Spitzer

Yael Mardor

David Guez

David Last

Yuval Barkan

Leor Zach

Dianne Daniels Elmakias

Shirley Sharabi

Lonia Kanelovitch

Noam Nissan

Maya Dadiani

Itzchak Yacov

Arie Rundstein

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.

Apparatus for analyzing brain MRI, is disclosed. The apparatus comprises an input for receiving a first and a second MRI scans at the beginning and end of a predetermined time interval post contrast administration; a subtraction map former for forming a subtraction map from said first and said second MRI scans by analyzing said scans to distinguish between two primary populations, a slow population, in which contrast clearance from the tissue is slower than contrast accumulation, and a fast population in which clearance is faster than accumulation; and an output to provide an indication of distribution of said two primary populations, wherein said predetermined time period is at least twenty minutes.

Magnetic resonance maps for analyzing tissue

A system and method for automated characterization of solid tumors using medical imaging. The system comprises an interface that is configured to acquire data from medical imaging devices, one or more processors, and an outputting device that reports the characterization of said solid tumor. The method of automated characterization, which is implemented by the system, acquires a sequence of images from the medical imager using a Dynamic Contrast Enhanced (DCE) imaging protocol, performs image registration, detects the contour of the solid tumor, and dividing the contours to segments. For each segment, the method calculating a displacement of the contrast material, fitting the displacement to a flow model and extracting an estimation of the interstitial fluid velocity. The estimated interstitial fluid velocity of the segments provide characterization of the solid tumor and includes an assessment of the tumor interstitial fluid pressure, the tumor drug delivery efficiency, and the tumor prognostic or metastasis risk.

System and method for automated characterization of solid tumors using medical imaging

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.

A method of processing an image having a plurality of picture-elements is disclosed. The method comprises: preprocessing the image to selectively enhance contrast of some picture-elements of the image, and employing a companding procedure for the preprocessed image, thereby providing a processed image. The contrast enhancement optionally and preferably features a mapping function having a plateau region for diminishing image data with intensity levels below an intensity threshold, thereby providing a preprocessed image.

Growing community of inventors

Mevasseret Zion, Israel

Miriam Sklair-Levy