Abstract: Automated determination of muscle mass from images can be carried by performing a thresholding process to an image file to generate a contrasted image, and segmenting pixels of the contrasted image into bone and not bone. The system can distinguish muscle from organ for the pixels segmented as not bone by determining a location of a rib cage of the patient using the pixels segmented as bone, and removing pixels segmented as not bone that are located within the location of the rib cage. The system can calculate a volume of muscle based on remaining pixels segmented as not bone; calculate a total muscle mass based on the volume of muscle; and provide the total muscle mass of the patient. The total muscle mass of the patient can then be used for applications including calculating a glomerular filtration rate.

Abstract: Automated determination of muscle mass from images can be carried by performing a thresholding process to an image file to generate a contrasted image, and segmenting pixels of the contrasted image into bone and not bone. The system can distinguish muscle from organ for the pixels segmented as not bone by determining a location of a rib cage of the patient using the pixels segmented as bone, and removing pixels segmented as not bone that are located within the location of the rib cage. The system can calculate a volume of muscle based on remaining pixels segmented as not bone; calculate a total muscle mass based on the volume of muscle; and provide the total muscle mass of the patient. The total muscle mass of the patient can then be used for applications including calculating a glomerular filtration rate.