Abdul Haseeb¹, Muhammad Attique Khan^1,*, Faheem Shehzad¹, Majed Alhaisoni², Junaid Ali Khan¹, Taerang Kim³, Jae-Hyuk Cha³

Computer Systems Science and Engineering, Vol.47, No.2, pp. 2397-2415, 2023, DOI:10.32604/csse.2023.040529

Abstract X-Ray knee imaging is widely used to detect knee osteoarthritis due to ease of availability and lesser cost. However, the manual categorization of knee joint disorders is time-consuming, requires an expert person, and is costly. This article proposes a new approach to classifying knee osteoarthritis using deep learning and a whale optimization algorithm. Two pre-trained deep learning models (Efficientnet-b0 and Densenet201) have been employed for the training and feature extraction. Deep transfer learning with fixed hyperparameter values has been employed to train both selected models on the knee X-Ray images. In the next step, fusion is performed using a canonical… More >

Xin Wang^*, Shuang Liu, Chang-Cai Zhou

Intelligent Automation & Soft Computing, Vol.37, No.1, pp. 221-234, 2023, DOI:10.32604/iasc.2023.036766

Abstract Knee osteoarthritis (OA) is a common disease that impairs knee function and causes pain. Currently, studies on the detection of knee OA mainly focus on X-ray images, but X-ray images are insensitive to the changes in knee OA in the early stage. Since magnetic resonance (MR) imaging can observe the early features of knee OA, the knee OA detection algorithm based on MR image is innovatively proposed to judge whether knee OA is suffered. Firstly, the knee MR images are preprocessed before training, including a region of interest clipping, slice selection, and data augmentation. Then the data set was divided… More >

Gang He^*

Molecular & Cellular Biomechanics, Vol.19, No.1, pp. 41-50, 2022, DOI:10.32604/mcb.2022.017044

Abstract This study aims to analyze the biomechanical difference between the two legs of male badminton players when they land on one leg, thereby providing some guidance for preventing sports injury. Ten male badminton players were selected as the subjects. They did the single-leg landing movement successfully three times. The kinematic data were obtained by the Vicon infrared high-speed motion capture system. The kinetic data were obtained by the KISTLER three-dimensional forcing measuring platform. The data were processed and analyzed. The center of gravity of the right leg on the X and Y axes were 0.25 ± 0.05 and 0.21 ± 0.04 m, respectively, which were… More >

G. Papaioannou¹, G. Nianios¹, C. Mitroyiannis¹, S.Tashman², K.H. Yang²

The International Conference on Computational & Experimental Engineering and Sciences, Vol.8, No.1, pp. 7-12, 2008, DOI:10.3970/icces.2008.008.007

Abstract Little is known about in vivo menisci loads and displacements in the knee during strenuous activities. We have developed a method that combines biplane high-speed dynamic radiography (DRSA) and a subject-specific finite element model for studying in vivo meniscal behavior. In a very controlled uniaxial compression loading condition, removing of the pressure sensor from the model can result in relatively large errors in contact and cartilage stress that are not reflected in the change of meniscal displacement. More >