Automated segmentation for acl revision operative planning

A non-transitory computer-readable storage medium tangibly encoded with computer-executable instructions, that when executed by a device, perform a method comprising:

• identifying, by the device, an image associated with a knee, the image depicting at least a portion of a femur and tibia after an initial anterior cruciate ligament (ACL) reconstruction procedure;
• analyzing, by the device, the image, and performing a first segmentation of the image, the first segmentation comprising information related to the femur and tibia, the first segmentation further comprising information related to tunnels associated with the initial ACL reconstruction procedure;
• further analyzing, by the device, the image, and performing a second segmentation of the image, the second segmentation comprising information related to hardware associated with the initial ACL reconstruction procedure;
• and
• generating, by the device, a three-dimensional (3D) model of the knee based on the first segmentation and the second segmentation.

A device comprising:

• a processor configured to:
• identify an image associated with a knee, the image depicting at least a portion of a femur and tibia after an initial anterior cruciate ligament (ACL) reconstruction procedure;
• analyze the image, and perform a first segmentation of the image, the first segmentation comprising information related to the femur and tibia, the first segmentation further comprising information related to tunnels associated with the initial ACL reconstruction procedure;
• further analyze the image, and perform a second segmentation of the image, the second segmentation comprising information related to a location of hardware associated with the initial ACL reconstruction procedure;
• and
• generate a three-dimensional (3D) model of the knee based on the first segmentation and the second segmentation.

A method comprising:

• identifying, by a device, an image associated with a knee, the image depicting at least a portion of a femur and tibia;
• analyzing, by the device, the image, and identifying information related to the femur and tibia;
• generating, by the device, based on the analysis, a segmentation image, the segmentation image comprising a depiction of the femur and tibia;
• identifying, by the device, a bone model for another knee, the bone model comprising information related to a femur, tibia and tunnels corresponding to an initial anterior cruciate ligament (ACL) reconstruction procedure;
• performing fitting, by the device, of the bone model to the segmentation image, the fitting comprising identification of the tunnels in relation to the femur and tibia of the segmentation image;
• and
• generating, by the device, a synthetic image based on the fitting of the bone model.