Spatially consistent multi-scale anatomical landmark detection in incomplete 3D-CT data

US10373313B2 · kind B2 · utility

Assignee

• Siemens Healthcare Limited · DE

Inventors

• Florin-Cristian Ghesu · Erlangen, DE
• Bogdan Georgescu · Plainsboro, US
• Sasa Grbic · Plainsboro, US
• Dorin Comaniciu · Princeton Junction, US

Key dates

• Filing date: Sep 5, 2017
• Grant date: Aug 6, 2019
• Expiry date: Dec 9, 2037

Classification

• Technology area (CPC G): Physics
• CPC primary: G06V2201/033
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

A method and system for automated spatially-consistent multi-scale detection of anatomical landmarks in medical images is disclosed. A discrete scale-space representation of a medical image of a patient is generated. A plurality of anatomical landmarks are detected at a coarsest scale-level of the discrete scale-space representation of the medical image using a respective trained search model trained at the coarsest scale-level for each of the plurality of anatomical landmarks. Spatial coherence of the detected anatomical landmarks is enforced by fitting a learned robust shape model of the plurality of anatomical landmarks to the detected anatomical landmarks at the coarsest scale-level to robustly determine a set of the anatomical landmarks within a field-of-view of the medical image. The detected landmark location for each of the landmarks in the set of anatomical landmarks is refined at each remaining scale-level of the discrete scale-space representation of the medical image using, for each landmark, a respective trained search model trained at each remaining scale-level and constrained based on the predicted landmark location at a previous scale-level.