公开(公告)号：US20250131250A1

公开(公告)日：2025-04-24

申请号：US18682408

申请日：2022-08-10

Applicant: VOLPARA HEALTH TECHNOLOGIES LIMITED ,  VOLPARA SOLUTIONS EUROPE LIMITED

Inventor： Kaier WANG ,  Ralph HIGHNAM

IPC: G06N3/0475 ,  G06T7/00

Abstract: A system and method, relates to the field of medical imaging and image translation. It relates, in particular, to means to translate a for-processing image to a for-presentation image that is manufacturer and modality agnostic. It is a system and method for learning a translation mapping between for-processing and for-presentation image pairs via a generative adversarial network (GAN) based deep learning system. The Generative Adversarial Network (GAN) comprises a first neural network as a generator and a second neural network as a discriminator configured to train one another to learn a translation mapping between sets of paired for-processing and for-presentation images.

公开(公告)号：US20210097677A1

公开(公告)日：2021-04-01

申请号：US15733058

申请日：2018-11-05

Applicant: VOLPARA HEALTH TECHNOLOGIES LIMITED

Inventor： Ralph HIGHNAM ,  Melissa HILL ,  Kaier WANG

IPC: G06T7/00 ,  G06T7/62 ,  G06K9/46 ,  G16H50/20 ,  G16H30/40 ,  A61B5/055 ,  A61B5/00

Abstract: A system and method for validating the accuracy of image parameters, especially for images used in the medical field. The system and method may be used for validating a native parameter from a source image of a source object, wherein: one or more native parameters from the source image is analysed with a reference data to determine whether the native parameter(s) is/are plausible.

公开(公告)号：US20250037281A1

公开(公告)日：2025-01-30

申请号：US18714065

申请日：2022-11-29

Applicant: VOLPARA HEALTH TECHNOLOGIES LIMITED

Inventor： Ralph HIGHNAM ,  Melissa HILL ,  Kaier WANG

IPC: G06T7/00 ,  G06T7/11 ,  G06T7/33 ,  G06V10/764

Abstract: A system and method are disclosed for quantitative evaluation of image acquisition quality within a field of view and derivation of associated qualitative metrics to inform interpretation. The medical image evaluation system comprises: a data input device to acquire data of medical images: and a data processor to perform an image segmentation on one or more of the medical image(s) of a body portion to delineate tissue(s) of interest from a surrounding region within a field of view. The data processor is configured to resolve any missing tissue which is any portion of the tissue(s) of interest missing from the image segmentation. The data processor is configured to quantify suitability of the medical images for interpretation by making an estimate of amount or location of the missing tissue. A data device is configured to advise a user of the quantified suitability of the medical images for interpretation.

公开(公告)号：US20220335602A1

公开(公告)日：2022-10-20

申请号：US17640762

申请日：2020-09-04

Applicant: VOLPARA HEALTH TECHNOLOGIES LIMITED

Inventor： Ralph HIGHNAM ,  Kaier WANG

IPC: G06T7/00 ,  G06T5/20 ,  G06T5/00 ,  G06T7/11 ,  G06T7/136

Abstract: The present invention relates to a method and system for the transformation of raw mammograms to normalised presentation and where the pixel values are independent of imaging conditions. The performed method includes: contrast enhancement, for improved visibility of the breast tissue composition, whereby a region of the breast is segmented and a contrast-stretching algorithm applied to the segmented region to preferably create an enhanced raw image or mammogram; local ‘maximum’ transform, whereby a 2-dimensional first filter is designed to extract the maximum pixel value from a region of interest (ROI) to preferably create a local maximum image or map; ratio map derivation, whereby the pixel value of the ratio map measures a relative response of the said pixel to its local maximum thus capturing the difference between breast composition regardless of mammogram variations.