Steven K Rogers

US Patent:

6389157, May 14, 2002

Filed:

Jan 11, 2001

Appl. No.:

09/758889

Inventors:

Steven K. Rogers - Beavercreek OH
Randy P. Broussard - Huber Heights OH
Edward M. Ochoa - San Antonio TX
Thomas F. Rathbun - Beavercreek OH
John E. Rosenstengel - Huber Heights OH

Assignee:

Qualia Computing, Inc. - Beavercreek OH

International Classification:

G06K 900

US Classification:

382132, 382260, 382270

Abstract:

A method and system for detecting and displaying clustered microcalcifications in a digital mammogram, wherein a single digital mammogram is first automatically cropped to a breast area sub-image which is then processed by means of an optimized Difference of Gaussians filter to enhance the appearance of potential microcalcifications in the sub-image. The potential microcalcifications are thresholded, clusters are detected, features are computed for the detected clusters, and the clusters are classified as either suspicious or not suspicious by means of a neural network. Thresholding is preferably by sloping local thresholding, but may also be performed by global and dual-local thresholding. The locations in the original digital mammogram of the suspicious detected clustered microcalcifications are indicated. Parameters for use in the detection and thresholding portions of the system are computer-optimized by means of a genetic algorithm.

US Patent:

6401082, Jun 4, 2002

Filed:

Nov 8, 1999

Appl. No.:

09/434549

Inventors:

Steven K. Rogers - Beavercreek OH
Mark E. Oxley - Dayton OH
Matthew Kabrisky - Dayton OH

Assignee:

The United States of America as represented by the Secretary of the Air Force - Washington DC

International Classification:

G06N 300

US Classification:

706 26, 706 25, 216 60

Abstract:

An efficient neural network computing technique capable of synthesizing two sets of output signal data from a single input signal data set. The method and device of the invention involves a unique integration of autoassociative and heteroassociative neural network mappings, the autoassociative neural network mapping enabling a quality metric for assessing the generalization or prediction accuracy of the heteroassociative neural network mapping.

US Patent:

6556699, Apr 29, 2003

Filed:

Aug 24, 2001

Appl. No.:

09/938908

Inventors:

Steven K. Rogers - Beavercreek OH
Philip Amburn - Dayton OH
Telford S. Berkey - London OH
Randy P. Broussard - Huber Heights OH
Martin P. DeSimio - Fairborn OH
Jeffrey W. Hoffmeister - Beavercreek OH
Edward M. Ochoa - San Antonio TX
Thomas P. Rathbun - Beavercreek OH
John E. Rosenstengel - Huber Heights OH

Assignee:

Qualia Computing, Inc. - Beavercreek OH

International Classification:

G06K 900

US Classification:

382132, 128922

Abstract:

A method and system for detecting and displaying clustered microcalcifications in a digital mammogram, wherein a single digital mammogram is first automatically cropped to a breast area sub-image which is then processed by means of an optimized Difference of Gaussians filter to enhance the appearance of potential microcalcifications in the sub-image. The potential microcalcifications are thresholded, clusters are detected, features are computed for the detected clusters, and the clusters are classified as either suspicious or not suspicious by means of a neural network. Thresholding is preferably by sloping local thresholding, but may also be performed by global and dual-local thresholding. The locations in the original digital mammogram of the suspicious detected clustered microcalcifications are indicated. Parameters for use in the detection and thresholding portions of the system are computer-optimized by means of a genetic algorithm.

US Patent:

6650766, Nov 18, 2003

Filed:

Oct 25, 2002

Appl. No.:

10/280237

Inventors:

Steven K. Rogers - Beavercreek OH
Philip Amburn - Dayton OH
Telford S. Berkey - London OH
Randy P. Broussard - West River MD
Martin P. DeSimio - Fairborn OH
Jeffrey W. Hoffmeister - Manhattan Beach CA
Edward M. Ochoa - Franklin OH
Thomas F. Rathbun - Monument CO
John E. Rosenstengel - Beavercreek OH

Assignee:

Qualia Computing, Inc. - Beavercreek OH

International Classification:

G06K 900

US Classification:

382132, 128922

Abstract:

A method and system for detecting and displaying clustered microcalcifications in a digital mammogram, wherein a single digital mammogram is first automatically cropped to a breast area sub-image which is then processed by means of an optimized Difference of Gaussians filter to enhance the appearance of potential microcalcifications in the sub-image. The potential microcalcifications are thresholded, clusters are detected, features are computed for the detected clusters, and the clusters are classified as either suspicious or not suspicious by means of a neural network. Thresholding is preferably by sloping local thresholding, but may also be performed by global and dual-local thresholding. The locations in the original digital mammogram of the suspicious detected clustered microcalcifications are indicated. Parameters for use in the detection and thresholding portions of the system are computer-optimized by means of a genetic algorithm.

US Patent:

6757415, Jun 29, 2004

Filed:

Jun 13, 2003

Appl. No.:

10/461301

Inventors:

Steven K. Rogers - Beavercreek OH
Kenneth W. Bauer - Fairborn OH
Michael J. Collins - Beavercreek OH
Martin P. DeSimio - Fairborn OH
Richard A. Mitchell - Springboro OH

Assignee:

Qualia Computing, Inc. - Beavercreek OH

International Classification:

G06K 900

US Classification:

382130, 382132

Abstract:

A computer aided detection method and system to assist radiologists in the reading of medical images. The method and system has particular application to the area of mammography including detection of clustered microcalcifications and densities. A microcalcification detector is provided wherein individual detections are rank ordered and classified, and one of the features for classification is derived using a multilayer perceptron. A density detector is provided including an iterative, dynamic region growing module with embedded subsystem for rank ordering and classification of a best subset of candidate masks. Features are computed from a detection on an input image by providing first and second regions on the input image corresponding to areas inside and outside the detection, measurements are computed based on values derived from the two regions, a standard deviation is computed for the measurements in each region, and a feature for the detection is computed using a Bauer-Fisher ratio. A post processing stage is provided where detections are analyzed in the context of a set of images for a patient. The final output of the system is a set of indications overlaid on the input medical images.

US Patent:

6763128, Jul 13, 2004

Filed:

Jun 13, 2003

Appl. No.:

10/461316

Inventors:

Steven K. Rogers - Beavercreek OH
Michael J. Collins - Beavercreek OH
Richard A. Mitchell - Springboro OH

Assignee:

Qualia Computing, Inc. - Beavercreek OH

International Classification:

B06K 900

US Classification:

382130, 378 37

Abstract:

A computer aided detection method and system to assist radiologists in the reading of medical images. The method and system has particular application to the area of mammography including detection of clustered microcalcifications and densities. A microcalcification detector is provided wherein individual detections are rank ordered and classified, and one of the features for classification is derived using a multilayer perceptron. A density detector is provided including an iterative, dynamic region growing module with embedded subsystem for rank ordering and classification of a best subset of candidate masks. A post processing stage is provided where detections are analyzed in the context of a set of images for a patient. The post processing includes a normalcy classification including providing computed values corresponding to each detection from a category of detections on an image set, computing a normalcy value using the computed values, and removing all detections from an image set when the normalcy value does not meet a predetermined condition. The final output of the system is a set of indications overlaid on the input medical images.

US Patent:

6778941, Aug 17, 2004

Filed:

Nov 13, 2001

Appl. No.:

10/010789

Inventors:

Steven W. Worrell - Dayton OH
Steven K. Rogers - Beavercreek OH
Matthew Kabrisky - Dayton OH
Philip Amburn - Dayton OH

Assignee:

Qualia Computing, Inc. - Beavercreek OH

International Classification:

G04F 100

US Classification:

702176, 709202, 709203, 709206, 709207, 715500, 7155011, 707100

Abstract:

A method and system for filtering messages where the importance of a message is determined by analyzing the message body in conjunction with message attributes. Message body refers to the text in the body of the message, whereas message attributes convey information about the message. In another embodiment, analysis of the users current computing environment provides additional input to the filtering system. This allows for preferentially weighting messages of users current interests. Analysis includes computation of feature vectors and subsequent input to a discriminant function. The discriminant function provides a test statistic which is compared to a threshold. If the test statistic exceeds the threshold, the incoming message is passed by the filtering system and may be displayed to the user. In another embodiment, message body and attributes are used to anticipate significant events in a time series, such as streaming financial data.

US Patent:

6801645, Oct 5, 2004

Filed:

Jun 23, 2000

Appl. No.:

09/602762

Inventors:

Michael J. Collins - Beavercreek OH
Steven K. Rogers - Beavercreek OH
Richard A. Mitchell - Springboro OH

Assignee:

iCad, Inc. - Nashua NH

International Classification:

G06K 900

US Classification:

382130, 382132, 378 37

Abstract:

A computer aided detection method and system to assist radiologists in the reading of medical images. The method and system has particular application to the area of mammography including detection of clustered microcalcifications and densities. A microcalcification detector is provided wherein individual detections are rank ordered and classified, and one of the features for classification is derived using a multilayer perceptron. A density detector is provided including an iterative, dynamic region growing module with embedded subsystem for rank ordering and classification of a best subset of candidate masks. A post processing stage is provided where detections are analyzed in the context of a set of images for a patient. Three analysis methods are used to distribute a limited number of detections across the image set and further within each image, and additionally to perform a normalcy classification. The normalcy classification is used to remove all detections from an image set when predetermined normalcy conditions are met.