University of Iowa Research Foundation

University of Notre Dame Du Lac

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

Xiaodong Wu

Michael D Abramoff

Milan Sonka

Danny Ziyi Chen

Shuang Luan

Xiaobo Sharon Hu

Yusung Kim

Cedric Xinsheng Yu

Chao Wang

Ryan T Flynn

Stephen Baek

Bryan G Allen

Mona K Garvin

Quentin E Adams

Karolyn M Hopfensperger

John Buatti

Yusen He

Brian J Smith

Yin Yin

Xiangmin Zhang

Li Tang

Kang Li

Methods and systems for image segmentation and analysis are described. A predictive model may be trained to identify and/or extract a rich set of image features with extensive prognostic value. For example, the predictive model may be trained to identify and/or extract features that that may be visualized to identify areas of interest (e.g., high-risk regions, etc.) within or adjacent to an object of interest, such a tumor. The predictive model may be trained to identify and/or extract features that that may predict a health related outcome, such as cancer patient survival/death, and modify therapeutic outcomes, such as diagnosis and treatment.

Methods and systems for image segmentation and analysis

Methods and systems are described for a rotating shield brachytherapy device. As disclosed herein, the rotating shield brachytherapy (RSBT) apparatus may comprise a radiation source, a drive assembly, a catheter, and an applicator. The applicator can have an outer surface and opposed proximal and distal end portions and a longitudinal axis extending along a length of the catheter. The distal end portion of the catheter can comprise one or more radiation shields and is configured to receive the radiation source. The drive assembly can be configured to engage the proximal end portion of the catheter to selectively rotate the catheter about the longitudinal axis.

Apparatus and method for rotating shield brachytherapy

Disclosed are systems and methods for image segmentation using convolutional networks. Image data comprising an image hypervolume can be received. The image hypervolume can be provided to a trained convolutional neural network (CNN). The CNN can output a segmentation of the image hypervolume.

System and method for n-dimensional image segmentation using convolutional neural networks

System and method for N-dimensional image segmentation using convolutional neural networks

Disclosed are methods and systems for analyzing data. An example method can comprise receiving volume data representative of an object. A first graph can be generated based on the volume data. The first graph can comprise nodes arranged in a Euclidean space. A deformation field can be determined based on the volume data. The deformation field can be applied to the first graph to form a second graph. The second graph can comprise nodes arranged in a non-Euclidean space. The second graph can be segmented.

Methods and systems for image analysis using non-euclidean deformed graphs

A system and methods for the efficient segmentation of globally optimal surfaces representing object boundaries in volumetric datasets is provided. An optical surface detection system and methods are provided that are capable of simultaneously detecting multiple interacting surfaces in which the optimality is controlled by the cost functions designed for individual surfaces and by several geometric constraints defining the surface smoothness and interrelations. The present invention includes surface segmentation using a layered graph-theoretic approach that optimally segments multiple interacting surfaces of a single object using a pre-segmentation step, after which the segmentation of all desired surfaces of the object are performed simultaneously in a single optimization process.

System and methods for multi-object multi-surface segmentation

A system and methods for the efficient segmentation of globally optimal surfaces representing object boundaries in volumetric datasets is provided. An optical surface detection system and methods are provided that are capable of simultaneously detecting multiple interacting surfaces in which the optimality is controlled by the cost functions designed for individual surfaces and by several geometric constraints defining the surface smoothness and interrelations. The graph search applications use objective functions that incorporate non-uniform cost terms such as 'on-surface' costs as well as 'in-region' costs.

System and methods for image segmentation in N-dimensional space

A system and methods for the efficient segmentation of globally optimal surfaces representing object boundaries in volumetric datasets is provided. An optical surface detection system and methods are provided that are capable of simultaneously detecting multiple interacting surfaces in which the optimality is controlled by the cost functions designed for individual surfaces and by several geometric constraints defining the surface smoothness and interrelations.

System and methods for image segmentation in n-dimensional space

The present invention provides a method comprising the following steps: (a) partitioning an intensity modulated beam into a set of sub-IMBs; and (b) partitioning the sub-IMBs into segments, wherein steps (a) and (b) introduce no machine delivery error. The present invention also provides a method comprising the following steps: (a) recursively partitioning an intensity modulated beam into plateaus; and (b) partitioning the plateaus into segments, wherein step (a) comprises determining a tradeoff between machine delivery error and the number of segments into which the plateaus will be partitioned in step (b).

Error control in algorithmic approach to step-and-shoot intensity modulated radiation therapy

The present invention provides a method comprising recursively partitioning an intensity modulated beam into plateaus; and partitioning the plateaus into segments. The present invention also provides a method for controlling administration of radiation therapy to a patient based on static leaf prescriptions. In addition, the present invention provides a method for partitioning an IMB.

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Coralville, IA, United States of America

Xiaodong Wu