The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
Nov. 09, 2010
Filed:
Oct. 10, 2006
Shaohua Kevin Zhou, Plainsboro, NJ (US);
Jie Shao, Sunnyvale, CA (US);
Jonathan Dowdall, Houston, TX (US);
Adrian Barbu, Plainsboro, NJ (US);
Bogdan Georgescu, Princeton, NJ (US);
Dorin Comaniciu, Princeton Junction, NJ (US);
Shaohua Kevin Zhou, Plainsboro, NJ (US);
Jie Shao, Sunnyvale, CA (US);
Jonathan Dowdall, Houston, TX (US);
Adrian Barbu, Plainsboro, NJ (US);
Bogdan Georgescu, Princeton, NJ (US);
Dorin Comaniciu, Princeton Junction, NJ (US);
Siemens Corporation, Iselin, NJ (US);
Abstract
The present invention is directed to a method for populating a database with a set of images of an anatomical structure. The database is used to perform appearance matching in image pairs of the anatomical structure. A set of image pairs of anatomical structures is received, where each image pair is annotated with a plurality of location-sensitive regions that identify a particular aspect of the anatomical structure. Weak learners are iteratively selected and an image patch is identified. A boosting process is used to identify a strong classifier based on responses to the weak learners applied to the identified image patch for each image pair. The responses comprise a feature response and a location response associated with the image patch. Positive and negative image pairs are generated. The positive and negative image pairs are used to learn a similarity function. The learned similarity function and iteratively selected weak learners are stored in the database.