Mayo Foundation for Medical Education and Research

Vanderbilt University

Brian J Bartholmai

Daniel J Blezek

Bradley J Erickson

Srinivasan Rajagopalan

Tobias Peikert

Ronald A Karwoski

Fabien Maldonado

Zachary Kelm

Systems and methods are provided for classifying a tissue mass as malignant or benign. The method includes identifying a region of interest in the tissue mass in computed tomography (CT) imaging data, segmenting the CT imaging data to delimit at least a portion of the tissue mass into image segments, extracting a set of radiomic parameters indicative of the tissue mass. The set of radiomic parameters may include tissue mass location, tissue mass shape, tissue mass surface characteristic, or tissue mass texture distribution indicative of the amount of image segments identified. The method also includes generating a report classifying the indeterminate lung nodule as being malignant or benign based on the set of radiomic parameters of the indeterminate lung nodule.

System and method for tomography-based radiomic mass analysis

A computer-implemented method for reducing noise in an image includes receiving a first image in a computer system. The first image depicts an interior of an item and is generated using a technique that provides imaging at selected depths in the item. The first image represents a first interior section having a first thickness. The method includes determining a modification for the first image using a second image of the interior. The second image represents a second interior section encompassing the first interior section and has a second thickness greater than the first thickness. The method includes storing the modification in association with the first image.

Reducing noise in an image

Growing community of inventors

Rochester, MN, United States of America

Brian J Bartholmai