Method for integrating image analysis, longitudinal tracking of a region of interest and updating of a knowledge representation
AssigneeToca, LLC
InventorsArmin Moehrle, Dirk Farin
Life of this patent
Estimating the term…
Abstract
A method for integrating image analysis, longitudinal tracking of a region of interest and updating of a knowledge representation, said method comprising the steps of: retrieving an image representation of a sample structure from an image database; automatically selecting a generic structure from a database containing a plurality of generic structures based on an imaging modality of the sample structure.
Claims18
1-14. (canceled)
A software implemented method for integrating image analysis, longitudinal tracking of data and updating of a knowledge representation, said method comprising the steps of:
- retrieving an image representation of a sample structure from an image database;
- automatically selecting a generic structure from a database based on an imaging modality of the sample structure, at least one knowledge representation stored in a second database, said knowledge representation being associated with said selected generic structure, the knowledge representation being specific to the imaging modality;
- mapping the selected generic structure to the sample structure;
- automatically determining at least one region of interest within the sample structure based on contents of the image representation of the sample structure or allowing the user to select a region of interest based on contents of the image representation of the sample structure;
- automatically selecting at least one diagnostic finding or allowing the user to select at least one diagnostic finding from a focused set knowledge representations based on the at least one region of interest and the imaging modality;
- retrievably storing the at least one diagnostic finding in a patient-specific electronic record;
- and
- dynamically monitoring each of the patient-specific electronic records for changes and using such changes to update the knowledge representation in the second database.
A method for progressively updating a knowledge representation, said method comprising a sequence of machine learning models ML_t, where ML_{t+1} is trained later in time than ML_t, each model ML_t trained based on a set of training data D_t consisting of training samples s_{t, i} with respective training weights w_{t, i}, each sample s_{t, i} that is similar to a sample s_{t−1, k } having a reduced weight w_{t, i}<w_{t−1, k}, and samples with updated outcome having an increased weight w_{t, i}>w_{t−1, k}.
Dependencies are inferred from the claim text.