University of Iowa Research Foundation

The United States Government as Represented by the Department of Veterans Affairs

Joseph M Reinhardt

Milan Sonka

Michael D Abramoff

Meindert Niemeijer

Eric A Hoffman

Geoffrey McLennan

Xiayu Xu

Juerg Tschirren

Sangyeol Lee

Soumik Ukil

Martin Donnelley

Deepa Gopalakrishnan

Melndert Niemeijer

Melissa Suter

Sarah E Gerard

The methods and systems provided can automatically determine an Arteriolar-to-Venular diameter Ratio, AVR, in blood vessels, such as retinal blood vessels and other blood vessels in vertebrates. The AVR is an important predictor of increases in the risk for stroke, cerebral atrophy, cognitive decline, and myocardial infarct.

Automated determination of arteriovenous ratio in images of blood vessels

Embodiments of the present systems and methods may provide fissure detection in CT images, with improved performance, accuracy, and specificity. For example, in an embodiment, a method may comprise imaging, using a computed tomography system, at least one lung, to generate, at a computer system comprising a processor, memory accessible by the processor, and computer program instructions stored in the memory and executable by the processor, at least one computed tomography image of the at least one lung, determining, at the computer system, at least one approximate fissure region of interest in the at least one lung image, determining, at the computer system, a more precise fissure location within the at least one region of interest, and generating an image of the lung including indication of the determined fissure location.

Fissurenet: a deep learning approach for pulmonary fissure detection in CT images

Devices, such as computer readable media, and methods, such as automated methods, for labeling and/or matching. Some of the devices and methods are particularly useful for anatomical labeling of human airway trees. Some of the devices and methods are particularly useful for matching branch-points of human airway trees from represented in two or more graphs.

Methods and devices for labeling and/or matching

Methods and systems for image registration implementing a feature-based strategy that uses a retinal vessel network to identify features, uses an affine registration model estimated using feature correspondences, and corrects radial distortion to minimize the overall registration error. Also provided are methods and systems for retinal atlas generation. Further provided are methods and systems for testing registration methods.

Optimal registration of multiple deformed images using a physical model of the imaging distortion

Methods and devices for airway tree labeling and/or matching

Automated methods for segmenting and smoothing volumes of interest, such as the mediastinal boundary of a lung. Devices and systems configured to perform the automated methods.

Methods of smoothing segmented regions and related devices

In one embodiment, a method that includes comparing a subject color medical image to normal color medical image data; and identifying abnormal pixels from the subject color medical image. Another embodiment includes a computer readable medium comprising machine readable instructions for implementing one or more steps of that method. Another embodiment includes a device that has a field programmable gate array configured to perform one or more of the steps of that method. Another embodiment includes a device that has an application specific integrated circuit configured to perform one or more of the steps of that method.

Methods and devices useful for analyzing color medical images

Growing community of inventors

Iowa City, IA, United States of America

Joseph M Reinhardt