Topogram Prediction from Surface Data in Medical Imaging
AssigneeSiemens Healthcare GmbH
InventorsBrian Teixeira, Vivek Kumar Singh, Birgi Tamersoy, Terrence Chen, Kai Ma, Andreas Krauss
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Abstract
For topogram predication from surface data, a sensor captures the outside surface of a patient. A generative adversarial network (GAN) generates the topogram representing an interior organ based on the outside surface of the patient. To further adapt to specific patients, internal landmarks are used in the topogram prediction. The topogram generated by one generator of the GAN may be altered based on landmarks generated by another generator.
Claims20
A method for topogram prediction from surface data in a medical imaging system, the method comprising:
- capturing, with a sensor, an outer surface of a patient;
- generating, by an image processor, the topogram by a machine-learned generative adversarial network in response to input of the surface data to the machine-learned generative adversarial network, the surface data being from an output of the sensor for the outer surface, the topogram representing an internal organ of the patient as a projection through the patient;
- and
- displaying, by a display device, the topogram.
A method for topogram prediction from surface data in a medical imaging system, the method comprising:
- capturing, with a sensor, an outer surface of a patient;
- generating, by an image processor, the topogram by first and second machine-learned networks in response to input of the surface data to the first and second machine-learned networks, the surface data being from an output of the sensor for the outer surface, the topogram representing an internal organ of the patient as a projection through the patient, the first machine-learned network outputting a spatial marker map, and the second machine-learned network outputting the topogram based on the surface data and the spatial marker map;
- and
- displaying, by a display device, the topogram.
A medical imaging system for topogram prediction, the medical imaging system comprising:
- a depth sensor configured to measure depths to a patient;
- an image processor configured to apply a machine-learned generator of a trained generative adversarial network to depth information from the depths, the machine-learned generator having been trained to generate the topogram from the depth information;
- and
- a display configured to display the topogram.
Dependencies are inferred from the claim text.