Insightful Corporation

Confirma, Inc.

Bradley Wyman

Lydia Ng

Vikram Chalana

Sayan Pathak

John Oelund

Christopher L Stork

Stephen Fogarasi

Steven Racki

Bobbi Sparks

A system for image registration and quantitative feature extraction for multiple image sets. The system includes an imaging workstation having a data processor and memory in communication with a database server in communication. The a data processor capable of inputting and outputting data and instructions to peripheral devices and operating pursuant to a software product and accepts instructions from a graphical user interface capable of interfacing with and navigating the imaging software product. The imaging software product is capable of instructing the data processor, to register images, segment images and to extract features from images and provide instructions to store and retrieve one or more registered images, segmented images, quantitative image features and quantitative image data and from the database server.

System and method for mining quantitive information from medical images

Computer-based methods and systems for automatically determining convergence when registering image sets are provided. Example embodiments provide an Enhanced Image Registration System (EIRS), which includes an Image Comparison Module, a Transformation Optimizer, and a Convergence Calculator. When the EIRS receives two image sets to align, the Image Comparison Module compares two image sets to determine or measure how closely the image sets are aligned. The Transformation Optimizer determines an appropriate transformation to apply to one of the image sets to align it with the reference image set. The Transformation Optimizer then applies the determined transformation. The Convergence Calculator examines one or more points within the transformed image set to determine when convergence is attained.

System and method for determining convergence of image set registration

A similarity value of data elements is modified to provide an improved image of an object. Using an appropriate sensor, data is collected from an object and stored as a plurality of discrete data points. The data points are compared to each other to determine how similar the data properties of one data element are to another data element. A similarity value is assigned to each of the data elements representative of the difference between the properties of the two data elements. The similarity value for each particular data element is then modified based on a weighted similarity value of the data element itself and a group of adjacent data elements. The modified similarity value is then stored for each data element and used to produce an image representative of the object.

Convolution filtering of similarity data for visual display of enhanced image

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Kirkland, WA, United States of America

Bradley Wyman