University of California

Hyun J Kim

Matthew S Brown

Jonathan Goldin

Corey W Arnold

Dieter R Enzmann

Yu Shi

Mahesh B Nagarajan

Weng Kee Wong

Jonathan G Goldin

A method for training a machine learning algorithm that classifies predictive regions-of interest ('ROI') of progression of idiopathic pulmonary fibrosis. The method includes acquiring a set of computed tomography (CT) images of a plurality of patients and selecting a plurality of ROIs within the set of images. Each of the ROIs designates a label that indicates progression of pulmonary fibrosis and training a machine learning algorithm by inputting the plurality of ROIs and the associated labels into the algorithm. The algorithm identifies the ROIs in the set of images as indicating regions of pulmonary fibrosis within the set of images based on the features.

System and method for prediction of disease progression of pulmonary fibrosis using medical images

A probability map of prostate tumor location is generated and displayed in response to receiving anatomic diagnostic medical imaging, such as from magnetic resonance (MR) scanning. A registration process is performed on the images in relation to a model built of prostate anatomy across different subjects in an enhanced prostate template. A probability map is created of tumor locations followed by transforming the imaging to incorporate the probability map and output a resultant image.

Apparatus and method for determining the spatial probability of cancer within the prostate

Automated image analysis systems and methods are disclosed to quantify change in fibrosis and interstitial lung disease. The system generates scoring changes in Quantitative Interstitial Lung Disease (QILD) by filtering the uploaded images to minimize cross-site variability within images, sampling from a grid of pixels or voxels within the CT images, classifying individual pixels or voxels within downloaded images based on one or more selected texture features, generating a QILD score for each image based on selected features within the image, and calculating a transition between QILD scores within the plurality of CT images.

Automated image system for scoring changes in quantitative interstitial lung disease

Growing community of inventors

Porter Ranch, CA, United States of America

Hyun J Kim