Early therapy response assessment of lesions

US9655563B2 · kind B2 · utility

Assignee

• Siemens Healthcare Limited · DE

Inventors

• David Liu · San Francisco, US
• Shaohua Kevin Zhou · Plainsboro, US
• Martin Paul Friedrich Kramer · Auckland, NZ
• Michael Sühling · Erlangen, DE
• Christian Tietjen · Ergolding, DE
• Grzegorz Soza · Heroldsberg, DE
• Andreas Wimmer · Graz, AT

Key dates

• Filing date: Aug 28, 2014
• Grant date: May 23, 2017
• Expiry date: Jul 11, 2035

Classification

• Technology area (CPC G): Physics
• CPC primary: G16H50/70
• WIPO field: Medical technology
• WIPO sector: Instruments

Abstract

For therapy response assessment, texture features are input for machine learning a classifier and for using a machine learnt classifier. Rather than or in addition to using formula-based texture features, data driven texture features are derived from training images. Such data driven texture features are independent analysis features, such as features from independent subspace analysis. The texture features may be used to predict the outcome of therapy based on a few number of or even one scan of the patient.