Method and apparatus for classifying a data point in imaging data
OwnerScott Anderson Middlebrooks, Henricus Wilhelm van der Heijden +1inventors
InventorsScott Anderson Middlebrooks, Henricus Wilhelm van der Heijden, Adrianus Cornelis Koopman
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Abstract
The invention provides a method and device for creating a model for classifying a data point in imaging data representing measured intensities, the method comprising: training a model using a first labelled set of imaging data points; determining at least one first image part in the first labelled set which the model incorrectly classifies; generating second image parts similar to at least one image part; further training the model using the second image parts. Preferably the imaging data points and the second image parts comprise 3D data points.
Claims13
Method for creating a model for classifying a data point in imaging data representing measured intensities, the method comprising:
- training a model using a first labelled set of imaging data points;
- determining at least one first image part in the first labelled set which the model incorrectly classifies;
- generating second image parts similar to at least one image part;
- further training the model using the second image parts, wherein
- the imaging data is 3-dimensional (3D) pixel data and the second image parts comprise 3D pixel data,
- the second image parts are generated by a generator model taking a latent vector as input, and
- the latent vector is determined corresponding to image part properties of interest.
Computation device comprising a processor in communication with a storage, the computation device configured for classifying a data point in imaging data representing measured intensities, by:
- training a model using a first labelled set of imaging data points;
- determining at least one first image part in the first labelled set which the model incorrectly classifies;
- generating second image parts similar to at least one image part;
- further training the model using the second image parts, wherein
- the imaging data is 3-dimensional (3D) pixel data and the second image parts comprise 3D pixel data,
- the second image parts are generated by a generator model taking a latent vector as input, and
- the latent vector is determined corresponding to image part properties of interest.
Dependencies are inferred from the claim text.