Systems and methods for segmentation of intra-patient medical images

A computer-implemented method for segmenting medical images, the method comprising the following operations performed by at least one processor:

• receiving one or more first medical images of an object, and a second medical image of the object, from a database configured to store a plurality of medical images acquired by an image acquisition device, each of the one or more first medical images associated with a first structure label map;
• registering each of the one or more first medical images and the first structure label map to the second medical image to generate a second structure label map;
• training a secondary classifier model using the registered second medical image and the corresponding second structure label map;
• merging the secondary classifier model with a primary classifier model to generate an updated primary classifier model;
• and
• determining an updated second structure label map associated with the second medical image using the updated primary classifier model.

A non-transitory computer-readable medium containing instructions that, when executable by a processor, cause the processor to perform a method for segmenting medical images, the method comprising:

• receiving one or more first medical images of an object, and a second medical image of the object, from a database configured to store a plurality of medical images acquired by an image acquisition device, each of the one or more first medical images associated with a first structure label map;
• registering each of the one or more first medical images and the first structure label map to the second medical image to generate a second structure label map;
• training a secondary classifier model using the registered second medical image and the corresponding second structure label map;
• merging the secondary classifier model with a primary classifier model to generate an updated primary classifier model;
• and
• determining an updated second structure label map associate with the second medical image using the updated primary classifier model.