Automatic learning of image features to predict disease

US7949167B2 · kind B2 · utility

Assignees

• Siemens Medical Solutions USA, Inc. · US
• Siemens Aktiengesellschaft · DE

Inventors

• Arun Krishnan · Plainsboro, US
• Xiang Zhou · Holmdel, US
• Martin Huber · Uttenreuth, DE
• Michael Kelm · Friedberg, DE
• Joerg Freund · Munich, DE

Key dates

• Filing date: Apr 22, 2009
• Grant date: May 24, 2011
• Expiry date: Dec 15, 2029

Classification

• Technology area (CPC G): Physics
• CPC primary: G06T2207/20081
• WIPO field: Computer technology
• WIPO sector: Electrical engineering

Abstract

A method for training a computer system for automatic detection of regions of interest includes receiving patient records. For each of the received patient records a text field and a medical image are identified from within the patient record and the medical image is automatically segmented to identify a structure of interest. The text field is searched for one or more keywords indicative of a particular abnormality associated with the structure of interest. The medical image is added to a grouping representing the particular abnormality when the text field indicates that the patient has the particular abnormality and the medical image is added to a grouping representing the absence of the particular abnormality when the text field does not indicate that the patient has the particular abnormality. The groupings of medical images are used to automatically train a computer system for the subsequent detection of the particular abnormality.