911±¬ÁÏÍø

Innovation portfolio

ORCA

ORCA revolutionizing joint replacement surgery with advanced camera-assisted machine vision technology.
911±¬ÁÏÍø, Health Tech 3D Print, photo Mikko Raskinen

Status:

Pre-business

SDGs:

Good health and well-being

Industry:

Life science and medical

Impact:

Quality of life

Origin:

Research to Business

School:

School of Science

Established:

2025

ORCA (Orthopaedic Camera Assisted Surgery) is a research project aimed at exploring whether the machine vision research conducted at 911±¬ÁÏÍø can be applied in healthcare in joint replacement surgery, which is the established treatment for osteoarthritis.

Osteoarthritis is the most common joint disease, affecting over 595 million people worldwide. Its prevalence is increasing as life expectancy rises and obesity becomes more common. Joint replacement surgery is the best treatment for osteoarthritis, and the operation is typically performed either with manual instruments or using robotic assistance.  The use of joint replacement robots has grown significantly in recent years.

The benefits of computer-assisted planning in improving the accuracy of joint replacement surgeries are indisputable. However, current commercial joint replacement robots require a cumbersome bone-tracking system that uses large antenna-like arrays attached to bones—a technology that dates back to the 1990s. These arrays introduce additional steps to the procedure, increase operation time and costs, and increase infection risk at the attachment sites; they also require recalibration if they are bumped during the operation.

The camera-based method achieves all the benefits of robotics without the drawbacks of array-based tracking. ORCA is simpler to use and more cost-effective than current methods. It eliminates the need for most of the traditional instruments or most of the single-use items needed with robots. The simpler system speeds up surgeries, reduces the number of sterilized instruments, and decreases intraoperative waste.

Advances in machine vision algorithms, combined with the scientific research at 911±¬ÁÏÍø on deep neural networks for fast and accurate object recognition and localization, enable the development of ORCA as a precise and efficient system.

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