Abstract: A method and an apparatus for automatic muscle segmentation are provided. The method includes receiving a high-resolution three-dimensional (3D) image obtained by a magnetic resonance imaging (MM) system and splitting the high-resolution 3D image into high-resolution 3D sub-images. Furthermore, the method includes acquiring low-resolution 3D sub-images of the high-resolution 3D sub-images and determining a boundary box within each corresponding low-resolution 3D sub-image. Moreover, the method includes determining a crop box for each boundary box, cropping each high-resolution 3D sub-image based on its corresponding crop box, and segmenting at least one muscle from the cropped box high-resolution 3D sub-image.

Abstract: The present disclosure relates to a method and apparatus for automatic muscle segmentation. The method includes: receiving a high-resolution three-dimensional (3D) image obtained by a magnetic resonance imaging (MRI) system; splitting the high-resolution 3D image into high-resolution 3D sub-images; acquiring low-resolution 3D sub-images of the high-resolution 3D sub-images; determining a boundary box within each corresponding low-resolution 3D sub-image; determining a crop box for each boundary box; cropping each high-resolution 3D sub-image based on its corresponding crop box; and segmenting at least one muscle from the cropped box high-resolution 3D sub-image.

Abstract: Some aspects of the present disclosure relate to identifying and profiling muscle patterns. In one embodiment, a method includes acquiring image data associated with a selected muscle or group of muscles of one or more subjects and determining, based on the image data, muscle volume of the selected muscle or group of muscles. The method also includes calculating, based on the muscle volume and the height and mass of the one or more subjects, a height-mass normalized muscle volume for the selected muscle or group of muscles, and determining a deviation of the height-mass normalized muscle volume of the selected muscle or group of muscles from a mean value of muscle volume associated with a corresponding reference muscle or reference group of muscles. The method also includes identifying, based on the deviation, a muscle abnormality or absence of a muscle abnormality in the selected muscle or group of muscles.