Method and system for detecting 3D anatomical structures using constrained marginal space learning

US8116548B2 · kind B2 · utility

Assignee

• Siemens Aktiengesellschaft · DE

Inventors

• Yefeng Zheng
• Bogdan Georgescu · Plainsboro, US
• Haibin Ling · College Park, US
• Michael Scheuering · Koblenzer Straße, DE
• Dorin Comaniciu · Princeton Junction, US

Key dates

• Filing date: May 26, 2009
• Grant date: Feb 14, 2012
• Expiry date: Jul 17, 2030

Classification

• Technology area (CPC G): Physics
• CPC primary: G06V2201/031
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

A method and apparatus for detecting 3D anatomical objects in medical images using constrained marginal space learning (MSL) is disclosed. A constrained search range is determined for an input medical image volume based on training data. A first trained classifier is used to detect position candidates in the constrained search range. Position-orientation hypotheses are generated from the position candidates using orientation examples in the training data. A second trained classifier is used to detect position-orientation candidates from the position-orientation hypotheses. Similarity transformation hypotheses are generated from the position-orientation candidates based on scale examples in the training data. A third trained classifier is used to detect similarity transformation candidates from the similarity transformation hypotheses, and the similarity transformation candidates define the position, translation, and scale of the 3D anatomic object in the medical image volume.