Numerical calibration approach for treatment couch calibration

A computer system, comprising:

• a processor;
• and
• a non-transitory computer-readable medium having stored thereon instructions that, when executed by the processor, cause the processor to perform the following:
• obtain multiple candidate datasets and multiple first couch models, wherein the multiple candidate sets include at least (a) a first dataset of multiple first calibration poses and (b) a second dataset of multiple second calibration poses;
• based on the multiple candidate sets and the multiple first couch models, perform numerical calibration to generate multiple second couch models;
• based on the multiple first couch models and the multiple second couch models, determine metric data associated with the multiple candidate datasets, wherein the metric data includes at least (a) first metric data associated with the first dataset and (b) second metric data associated with the second dataset;
• and
• select, from the multiple candidate datasets, the first dataset based on the metric data, wherein the first dataset is selected for use by a controller associated with a treatment couch to cause the treatment couch to move towards each of the multiple first calibration poses during treatment couch calibration.

A radiation therapy system, comprising:

• a treatment couch that requires calibration;
• and
• a couch calibration system to:
• obtain a selected dataset of multiple calibration poses that is selected from multiple candidate datasets based on metric data associated with the multiple candidate datasets, wherein (a) numerical calibration is performed based on the multiple candidate datasets and multiple first couch models to generate multiple second couch models, and (b) the metric data is generated based on the multiple first couch models and the multiple second couch models;
• and
• perform couch calibration based on the selected dataset by (a) instructing the treatment couch to move towards each of the multiple calibration poses in the selected dataset, (b) estimating measured pose data associated with the multiple calibration poses, and (c) determining geometric correction data associated with the treatment couch based on the measured pose data.