AI-based atlas mapping slice localizer for deep learning autosegmentation
US12141966B2 · kind B2 · utility
Assignee
Inventors
Key dates
| Filing date | Sep 28, 2021 |
| Grant date | Nov 12, 2024 |
| Priority date | — |
| Expiry date | Nov 27, 2042 |
Classification
- Technology area (CPC G)Physics
- CPC primaryG06T2207/30004
- WIPO fieldComputer technology
- WIPO sectorElectrical engineering
Abstract
Embodiments described herein provide a method for generating training data for Al based atlas mapping slice localization, and a system and method for using the training data to train a deep learning network. Training data development maps each slice of an input medical image to a position in a full body reference atlas along the longitudinal body axis. The method constructs a landmarking table of 2D slices indicating known anatomic landmarks of a reference subject, and interpolated slices. A final step for obtaining training data uses regression analysis techniques to create a vector of longitudinal axis coordinates of all slices from the input image. The training data is used to train a deep learning model to create an AI-based atlas mapping slice localizer model. The trained AI-based atlas mapping slice localizer model can be applied to generate mapping inputs to autosegmentation models to improve efficiency and reliability of contouring.
Source: USPTO / EPO open patent data. Objective bibliographic and citation counts.