Abstract: The present disclosure provides a method and system using software and associated equipment to automatically identify two or more preselected anatomical features by examining pixels within images, such as computerized tomography (CT) scanned images, determining appropriate measurements between such identified features based on dimensions and scaling available within the image file, comparing these measurements to normative data, and providing output of the results to a user, such as medical personnel. In at least one embodiment, the system can measure an interval between a first bone and a second bone that may be useful for medical analysis.

Abstract: The present disclosure provides a method and system using software and associated equipment to automatically identify two or more preselected anatomical features by examining pixels within images, such as computerized tomography (CT) scanned images, determining appropriate measurements between such identified features based on dimensions and scaling available within the image file, comparing these measurements to normative data, and providing output of the results to a user, such as medical personnel. In at least one embodiment, the system can measure an interval between a first anatomical feature and a second anatomical feature that may be useful for medical analysis.

Abstract: The present disclosure provides a method and system using software and associated equipment to automatically identify two or more preselected anatomical features by examining pixels within images, such as computerized tomography (CT) scanned images, determining appropriate measurements between such identified features based on dimensions and scaling available within the image file, comparing these measurements to normative data, and providing output of the results to a user, such as medical personnel. In at least one embodiment, the system can measure an interval between a first bone and a second bone that may be useful for medical analysis.

Abstract: The present disclosure provides a method and system using software and associated equipment to automatically identify two or more preselected anatomical features by examining pixels within images, such as computerized tomography (CT) scanned images, determining appropriate measurements between such identified features based on dimensions and scaling available within the image file, comparing these measurements to normative data, and providing output of the results to a user, such as medical personnel. In at least one embodiment, the system can measure an interval between a first anatomical feature and a second anatomical feature that may be useful for medical analysis.

Abstract: The present disclosure provides a method and system using software and associated equipment to automatically identify two or more preselected anatomical features by examining pixels within images such as computerized tomography (CT) scanned images, determining appropriate measurements between such identified features based on dimensions and scaling available within the image file, comparing these measurements to normative data, and providing output of the results to a user, such as medical personnel. In at least one embodiment, system can measure the basion-dens interval (BDI), which has been shown to be an effective indicator of ligament injury within the occipito-cervical complex (“OCC”) that may not present with other symptoms, is not revealed with standard CT imaging, and is of mortal danger to the patient if untreated. The system can automate interpreting CT scanned images and alert medical personnel about the risk of OCC ligament damage.

Abstract: The present disclosure provides a method and system using software and associated equipment to automatically identify two or more preselected anatomical features by examining pixels within images such as computerized tomography (CT) scanned images, determining appropriate measurements between such identified features based on dimensions and scaling available within the image file, comparing these measurements to normative data, and providing output of the results to a user, such as medical personnel. In at least one embodiment, system can measure the basion-dens interval (BDI), which has been shown to be an effective indicator of ligament injury within the occipito-cervical complex (“OCC”) that may not present with other symptoms, is not revealed with standard CT imaging, and is of mortal danger to the patient if untreated. The system can automate interpreting CT scanned images and alert medical personnel about the risk of OCC ligament damage.

Abstract: An infrared signature suppression system for reducing infrared radiation emitted by a vehicle. The system includes an elongate duct mounted on the vehicle having a hollow interior extending along an axial centerline between an upstream end and a downstream end for transporting exhaust gas emitted by the vehicle, and a baffle positioned in the hollow interior of the duct between the upstream end and the downstream end. At least a portion of at least one of the duct and the baffle includes an emissivity coating for reducing infrared radiation emitted by the vehicle.

Abstract: An infrared signature suppression system for reducing infrared radiation emitted by a vehicle. The system includes an elongate duct mounted on the vehicle having a hollow interior extending along an axial centerline between an upstream end and a downstream end for transporting exhaust gas emitted by the vehicle, and a baffle positioned in the hollow interior of the duct between the upstream end and the downstream end. At least a portion of at least one of the duct and the baffle includes an emissivity coating for reducing infrared radiation emitted by the vehicle.