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 - 28 July 2023

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… More >

Abdul Qadir¹, Rabbia Mahum¹, Suliman Aladhadh^2,*

Computer Systems Science and Engineering, Vol.47, No.2, pp. 1365-1384, 2023, DOI:10.32604/csse.2023.037033 - 28 July 2023

Abstract A considerable portion of the population now experiences osteoarthritis of the knee, spine, and hip due to lifestyle changes. Therefore, early treatment, recognition and prevention are essential to reduce damage; nevertheless, this time-consuming activity necessitates a variety of tests and in-depth analysis by physicians. To overcome the existing challenges in the early detection of Knee Osteoarthritis (KOA), an effective automated technique, prompt recognition, and correct categorization are required. This work suggests a method based on an improved deep learning algorithm that makes use of data from the knee images after segmentation to detect KOA and… 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 - 29 April 2023

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… More >

Sang-min Lee^*, Namgi Kim

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1981-1994, 2023, DOI:10.32604/cmc.2023.035245 - 06 February 2023

Abstract Artificial intelligence technologies are being studied to provide scientific evidence in the medical field and developed for use as diagnostic tools. This study focused on deep learning models to classify degenerative arthritis into Kellgren–Lawrence grades. Specifically, degenerative arthritis was assessed by X-ray radiographic images and classified into five classes. Subsequently, the use of various deep learning models was investigated for automating the degenerative arthritis classification process. Although research on the classification of osteoarthritis using deep learning has been conducted in previous studies, only local models have been used, and an ensemble of deep learning models… More >

Mohamed Yacin Sikkandar^1,*, S. Sabarunisha Begum², Abdulaziz A. Alkathiry³, Mashhor Shlwan N. Alotaibi¹, Md Dilsad Manzar⁴

CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 4279-4291, 2022, DOI:10.32604/cmc.2022.020571 - 11 October 2021

Abstract Knee Osteoarthritis (KOA) is a degenerative knee joint disease caused by ‘wear and tear’ of ligaments between the femur and tibial bones. Clinically, KOA is classified into four grades ranging from 1 to 4 based on the degradation of the ligament in between these two bones and causes suffering from impaired movement. Identifying this space between bones through the anterior view of a knee X-ray image is solely subjective and challenging. Automatic classification of this process helps in the selection of suitable treatment processes and customized knee implants. In this research, a new automatic classification More >