X-ray based machine vision system for distal locking of intramedullary nails

In surgical procedures for femoral shaft fracture treatment, current techniques for locking the distal end of intramedullary nails, using two screws, rely heavily on the use of two-dimensional X-ray images to guide three-dimensional bone drilling processes. Therefore, a large number of X-ray images are required, as the surgeon uses his/her skills and experience to locate the distal hole axes on the intramedullary nail. The long-term effects of X-ray radiation and their relation to different types of cancer still remain uncertain. Therefore, there is a need to develop a surgical technique that can limit the use of X-rays during the distal locking procedure. A Robotic-Assisted Orthopaedic Surgery System has been developed at Loughborough University named Loughborough Orthopaedic Assistant System (LOAS) to assist orthopaedic surgeons during distal-locking of intramedullary nails. It uses a calibration frame and a C-arm X-ray unit. The system simplifies the current approach as it uses only two near-orthogonal X-ray images to determine the drilling trajectory of the distal-locking holes, thereby considerably reducing irradiation to both the surgeon and patient. The LOAS differs from existing computer-assisted orthopaedic surgery systems, as it eliminates the need for optical tracking equipment which tends to clutter the operating theatre environment and requires care in maintaining the line of sight. Additionally use of optical tracking equipment makes such systems an expensive method for surgical guidance in distal-locking of intramedullary nails. This study is specifically concerned with the improvements of the existing system. [Continues.

X-ray-based machine vision system for distal locking of intramedullary nails

In surgical procedures for femoral shaft fracture treatment, current techniques for locking the distal end of intramedullary nails, using two screws, rely heavily on the use of two-dimensional X-ray images to guide three-dimensional bone drilling processes. Therefore, a large number of X-ray images are required, as the surgeon uses his/her skills and experience to locate the distal hole axes on the intramedullary nail. The long-term effects of X-ray radiation and their relation to different types of cancer still remain uncertain. Therefore, there is a need to develop a surgical technique that can limit the use of X-rays during the distal locking procedure. A robotic-assisted orthopaedic surgery system has been developed at Loughborough University to assist orthopaedic surgeons by reducing the irradiation involved in such operations. The system simplifies the current approach as it uses only two near-orthogonal X-ray images to determine the drilling trajectory of the distal locking holes, thereby considerably reducing irradiation to both the surgeon and patient. Furthermore, the system uses robust machine vision features to reduce the surgeon's interaction with the system, thus reducing the overall operating time. Laboratory test results have shown that the proposed system is very robust in the presence of variable noise and contrast in the X-ray images

Automated people-counting by using low-resolution infrared and visual cameras

Non-contact counting of people in a specified area has many applications for safety, security and commercial purposes. Visible sensors have inherent limitations for this task, being sensitive to variations in ambient lighting and colours in the scene. Infrared imaging can overcome many of these problems, but normally hardware costs are prohibitively expensive. A system for counting people in a scene using a combination of low cost, low-resolution visual and infrared cameras is presented in this paper. The aim of this research was to assess the potential accuracy and robustness of systems using low-resolution images. This approach results in considerable savings on hardware costs, enabling the development of systems which may be implemented in a wide range of applications. The results of 18 experiments show that the system can be accurate to within 3% over a wide range of lighting conditions