Preprocessing medical image data for machine learning

US11861839B2 · kind B2 · utility

Assignee

• KONINIKLIJKE PHILIPS N.V. · NL

Inventors

• Rolf Jürgen Weese · Norderstedt, DE
• Alexandra Groth · Hamburg, DE
• TOM BROSCH · Hamburg, DE
• Jochen Peters · Norderstedt, DE

Key dates

• Filing date: May 8, 2019
• Grant date: Jan 2, 2024
• Expiry date: Feb 6, 2041

Classification

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

Abstract

A system and computer-implemented method are provided for preprocessing medical image data for machine learning. Image data is accessed which comprises an anatomical structure. The anatomical structure in the image data is segmented to obtain a segmentation of the anatomical structure as a delineated part of the image data. A grid is assigned to the delineated part of the image data, the grid representing a partitioning of an exterior and interior of the type of anatomical structure using grid lines, wherein said assigning comprises adapting the grid to fit the segmentation of the anatomical structure in the image data. A machine learning algorithm is then provided with an addressing to the image data in the delineated part on the basis of coordinates in the assigned grid. In some embodiments, the image data of the anatomical structure may be resampled using the assigned grid. Advantageous, a standardized addressing to the image data of the anatomical structure is provided, which may reduce the computational overhead of the machine learning, require fewer training data, etc.