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Medical Science

Statistically, on an average, about nine joint replacement surgeries took place each day in Singapore in 2013. This number is expected to rise steadily in the years to come. This heralds a foreseeable strain on the healthcare system.

To ensure that the quality of life is not compromised, prosthesis needs to be provided in the shortest time possible and to the closest accuracy to each patient’s body. This is now possible with an increasingly automated production of custom-made prosthetic devices.

High pressures on the system

According to the American Academy of Orthopedic Surgeons, about 10 percent of joint replacement surgeries in America fail and require revision surgery.[2]. Accuracy is crucial to the success of joint replacement surgery. A prosthesis that does not fit accurately into a joint runs the risk of dislocation or worse still, the body rejecting it. Running smoothly: Fast and effective joint replacements to achieve the right fit, surgeons utilize Magnetic Resonance (MR) or Computed Tomography (CT) scans to identify and differentiate between bone and soft tissue. Based on the scans, technicians then have to manually demarcate points along bone edges to achieve precise bone boundary delineation. The precise segmentation is crucial to enable theplan for the manufacture of a jig that best suits the patient.This is the most important, yet time and labor consuming stage that usually takes a few hours to complete before it even moves on to the actual production of the personalized jig.

With so many delicate details embedded in the processes, the healthcare system needs an end-to-end solution that is able to handle both the intricacies of prosthesis planning and manufacturing, and the speed at which they are produced.

Streamlining the process Automated 3-D image segmentation

Instead of medical technicians spending hours on the drawing board demarcating where to cut along the bone, software applications are now able to replace this laborious task.

Trained on thousands of images annotated by experts, the software program learns to identify so-called “landmarks” – characteristics that are common to all examples of a target group. From an archive of patient scans, the system learns the model of each joint, internalizing the relationship between each image and its anatomical context.

The bone identification system automatically studies the scans and separates the bone from the soft tissue three dimensionally and produces all associated 3-D bone representations such as 3-D meshes right down to a granularity of about 0.5mm, all in under a minute.This not only saves time, but machines also improve on precision with each 3-D image segmentation.

Customized virtual surgical cutting guides

After image segmentation is done, the actual planning to production of prosthesis is another lengthy process. The slightest error will result in a prosthesis not closely fitted to the patient’s need, and could hugely impact the patient’s quality of life. This can be avoided by first simulating and optimizing everything in the virtual world to avoid possibility of errors on the operating table.

Custom surgical guides, or 3-D jigs, are now available for use by surgeons to prepare a bone for prosthesis. The jig can include holes for the precise positioning and angulation of screws,

optimizing the installation of a prosthesis. Surgical plans are produced and reviewed by surgeons along the way before manufacturing instructions are sent for the production of the jig. Once surgeons and the machine are familiar with the program, the surgical cutting guides can be produced automatically from start to end.




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