Yosuke Uozumi

Six degree of freedom calculation based on principal component analysis for the knee joint in MDCT image

The anterior cruciate ligament (ACL) injury can cause a reason of instability along anterior — posterior translation at extension. Thus, it is important to examine the knee joint quantitatively for understanding clinical outcome. However, an quantitative calculation method of the knee joint has not been reported. Therefore, we have developed six degree of freedom (6 DOF) calculation based on principal component analysis (PCA) for the knee joint in multi-detecter row computer tomography (MDCT) image. The proposal method was applied to six ACL injured knees obtained at two periods. As a result, the proposed methods could calculated 6 DOF of the knee joint quantitatively.

An Automated Analysis for Anatomical Structure of Distal Femur from MDCT Image by Contour Tracing

Comparison of anatomical or functional parameters is common theme in the evaluation of unilateral pathologies of the human knee joint, although the degree of bilateral symmetry is unknown. Currently, the evaluation is performed manually. Therefore, diversity of the evaluation happens due to the subjective judgment. To reduce the diversity, we propose an automated analysis method for anatomical knee structure from multi-detector row computerized tomography (MDCT) image. The experiment employed six different knees. Then, symmetry data were made from the six raw data by using mirroring processing. The six raw data and six mirroring data were evaluated by the proposed and manual method. The results of the proposed method indicated that there was no difference between the raw and mirroring data, while the results of the manual method clarified that there is almost two mm difference between them. It is concluded that the proposed method could identify the anatomical structure with no difference between bilateral knees.

An automatic bone segmentation method based on anatomical structure for the knee joint in MDCT image

The purpose of this study is to propose an automatic segmentation about each bone (the femur, the tibia, the patellar, and fibular) of the knee in MDCT image. The proposed method was applied for six patients (Age 33 ± 13, four males / tew females). The proposed method segmented the knee joint into each bone by using anatomical structure for the knee joint. The experiments calculate matching rate of the manual and the proposed method for evaluating it. As a result, The matching rate of the femur, the tibia, the patellar, and fibula were 95.84 ± 0.57%, 94.12 ± 1.01%, 94.49 ± 0.83%, 86.37 ± 4.28%, respectively. This study concluded that the proposed method is enough to segment the knee bones.

Automation of the Simple Test for Evaluating Hand Function Using Leap Motion Controller

In the test to evaluate the upper limb function, there is Simple Test for Evaluating Hand Function (STEF). This test is performed for one subject by one examiner. When the subject moves to grab the object, it is evaluated with the accuracy and speed. However STEF has problems that takes labor and massive time. In addition human error happens due to huge data management. In order to solve these problems, this study proposes an automated system of the simple test for evaluating hand function using Leap Motion controller to conduct a STEF on the PC screen. Leap Motion controller is a sensor that focuses on only the finger and hand motions. The proposed system could automatically evaluat the hand motion of the subjects by moving virtual objects on the screen. As a future challenge, there is a need to evaluate attracting upper limb function disabilities.

An Automatic Segmentation of Bone Tunnels after Anterior Cruciate Ligament Reconstruction in MDCT Image Using K-means Clustering☆

Abstract The anterior cruciate ligament (ACL) reconstruction is usually performed for the injured knee. The ACL reconstruction needs two bone tunnels. It is important to measure changing of the bone tunnel regions after surgery. Thus this study aims to propose an automated segmentation about anteromedial (AM) and posterolateral (PL) parts of the bone tunnels after double bundle ACL reconstruction using k-means clustering. Six patients were evaluated (Age 27 ± 7, four males/two females). As a result, this method could be divided for all patients. This study concluded that the proposed method is enough to divide the bone tunnels of double bundle technique after ACL reconstruction.

Computer-Aided Segmentation System of Posterior Cruciate Ligament in Knee Joint from CT and MRI Using Anatomical Information: A Pilot Study of System Configuration

Posterior cruciate ligament (PCL) is important for the knee stability. The problem seems to lie in the fact that it is difficult to segment the PCL from a magnetic resonance (MR) image. To reduce massive measurement time and subjective judgment error, this paper proposes a segmentation method of the PCL in knee joint from MR image and computed tomography (CT) image using anatomical information. In the experiment, a normal knee was analyzed by the proposed method. In the result, the segmented PCL was visually observed. We concluded that the proposed method can segment the PCL from the knee MR image.

A Virtual Reality System for Occupational Therapy with Hand Motion Capture and Force Feedback

This study proposes a virtual reality system for occupational therapy with hand motion capture and force feedback. Force feedback is realized by using a vibration motor. In the experiment, the proposed system was applied for three health males. The results with force feedback were close to the setting distance more than the results without force feedback. As a future work, actual working task used in clinical situation should be applied to this system.

3D interactive trace teaching system with anatomical model

Total knee arthroplasty (TKA) is an effective surgical treatment for the knee osteoarthritis, and is currently performed about 50,000 per year in Japan. TAK minimally invasive surgery (TKA-MIS) is a smaller incision range than TKA, and can expect an early recovery and post-surgical pain reduction. The navigation system for the purpose of precision improvement and shortening of the operative time operated on has been already studied. However, a study for the instruction system to improve the skill of surgeons has not yet advanced. This study aims to develop a training system which can makes non-expert surgeon improved the skill by simulating the TKA-MIS. The proposed method developed a simulator for the knee model with a three-dimensional electromagnetism sensor. The experiment established an evaluation method for the skin incision by tracing a sham scalpel trace. The developed system was applied to one non-experts. In the experimental results, non-teaching case was 65.80+/-7.00; teaching case, 83.44+/-11.04 (p = 0.00 <; 0.05, student t-test). The experimental result leads to the conclusion that the proposed training system has the learning effect.

Automated extraction of tibial eminence in CT image using shape matching

There is the tibial eminence at the tibial plateau which often fractures in early age. Medical doctors subjectively diagnose the injury with multi-detector computed topography (MDCT) image. However, the evaluation results depends on the knowledge and experience. It is important to provide a quantitative criterion to them. A purpose of this study is to propose an automated extraction of the tibial eminence in MDCT image using shape matching. In the experiments, the proposed method evaluated six patients (Age 27 ± 7, four males / two females). As a result, the proposed method could automatically extract the eminence shape for all the patients. This study concluded that the proposed method is enough to provide a quantitative criterion about the tibial eminence.

An analysis of EndoButton displacement and attitude in anterior cruciate ligament reconstruction using bone tunnel axis

EndoButton is a fixation device which is attached to an end point of the bone tunnel in the anterior cruciate ligament (ACL) reconstruction. Displacement of the EndoButton affects the clinical outcome. Analysis of the EndoButton displacement can support to avoid the misplacement. This study set the goal to propose an analysis of EndoButton attitude after anterior cruciate ligament reconstruction (ACL) in knee CT image. In the experiments, the proposed method was applied to 15 EndoButtons with the single and double bundle techniques of ACL reconstruction. The result shows a correlation between displacement length and attitude of EndoButton (r = -0.727, N = 9, p = 0.027 <; 0.05). This study has concluded that the proposed method can quantitatively analyze the EndoButton attitude from the CT image after the ACL reconstruction and the EndoButton might displace relative to the attitude between time-zero and follow-up.