Affatato S. 2 - biomechanics of the knee. In: Affatato, S. (ed.) Surgical Techniques in Total Knee Arthroplasty and Alternative Procedures, pp. 17–35. Woodhead Publishing, Oxford; 2015. https://doi.org/10.1533/9781782420385.1.17 . https://www.sciencedirect.com/science/article/pii/B9781782420309500026

Flandry F, Hommel G. Normal anatomy and biomechanics of the knee. Sports Med Arthrosc Rev. 2011;19(2):82–92.

Article  MATH  Google Scholar 

Kanamoto T, Mae T, Yokoyama T, Tanaka H, Ebina K, Nakata K. Significance and definition of early knee osteoarthritis. Ann Joint. 2020;5:4.

Article  Google Scholar 

Ramazanian T, Fu S, Sohn S, Taunton MJ, Maradit Kremers H. Prediction models for knee osteoarthritis: review of current models and future directions. Arch Bone Joint Surg. 2023;11(1):1–10.

Google Scholar 

Saeed A, Zulfiqar T, Kaleem M, Hafeez M, Ghauri MW. Health related quality of life in patients with grade iii knee osteoarthritis. Rawal Med J. 2021;46(3):580–3.

Google Scholar 

Das SK, Farooqi A. Osteoarthritis. Best Pract Res Clin Rheumatol. 2008;22(4):657–75. https://doi.org/10.1016/j.berh.2008.07.002. (Musculoskeletal Conditions in the Developing World).

Article  Google Scholar 

Taj Din S. Factors affecting the extent of utilization of physiotherapy services among orthopedic consultants in lahore, pakistan. Clin Surg. 2021;5(7):1–7.

Google Scholar 

Shakeel R, Khan AA, Ayyub A, Masood Z. Impact of strengthening exercises with and without blood flow restriction on quadriceps of knee osteoarthritis patients. J Pak Med Assoc. 2021;71(9):2173–6.

MATH  Google Scholar 

Khan RM, Albutt K, Qureshi MA, Ansari Z, Drevin G, Mukhopadhyay S, Khan MA, Chinoy MA, Meara J, Hussain H. Time-driven activity-based costing of total knee replacements in karachi, pakistan. BMJ Open. 2019;9(5): 025258.

Article  Google Scholar 

Teoh YX, Lai KW, Usman J, Goh SL, Mohafez H, Hasikin K, Qian P, Jiang Y, Zhang Y, Dhanalakshmi S. Discovering knee osteoarthritis imaging features for diagnosis and prognosis: Review of manual imaging grading and machine learning approaches. Journal of Healthcare Engineering 2022; 2022.

Cui A, Li H, Wang D, Zhong J, Chen Y, Lu H. Global, regional prevalence, incidence and risk factors of knee osteoarthritis in population-based studies. EClin Med. 2020;29: 100587.

Google Scholar 

Iqbal MN, Haidri FR, Motiani B, Mannan A. Frequency of factors associated with knee osteoarthritis. JPMA-J Pak Med Assoc. 2011;61(8):786.

Google Scholar 

Tariq T, Suhail Z, Nawaz Z. Machine learning approaches for the classification of knee osteoarthritis. In: The 3rd International Conference on Electrical, Computer, Communications and Mechatronics Engineering (ICECCME); 2023. IEEE.

Brahim A, Jennane R, Riad R, Janvier T, Khedher L, Toumi H, Lespessailles E. A decision support tool for early detection of knee osteoarthritis using x-ray imaging and machine learning: Data from the osteoarthritis initiative. Comput Med Imaging Graph. 2019;73:11–8.

Article  Google Scholar 

Hill JR, Oei EH, Crossley KM, Menz HB, Macri EM, Smith MD, Wyndow N, Maclachlan LR, Ross MH, Collins NJ. Contemporary methods of acquiring patellofemoral joint radiographs: a scoping review. Osteoarthritis Imaging. 2022;2(1): 100008.

Article  Google Scholar 

Luyten FP, Denti M, Filardo G, Kon E, Engebretsen L. Definition and classification of early osteoarthritis of the knee. Knee Surg Sports Traumatol Arthrosc. 2012;20:401–6.

Article  Google Scholar 

Yick HTV, Chan PK, Wen C, Fung WC, Yan CH, Chiu KY. Artificial intelligence reshapes current understanding and management of osteoarthritis: A narrative review. J Orthop Trauma Rehabilit. 2022;29(1):22104917221082316.

Article  Google Scholar 

Saini D, Chand T, Chouhan DK, Prakash M. A comparative analysis of automatic classification and grading methods for knee osteoarthritis focussing on x-ray images. Biocybernetics and Biomedical Engineering; 2021.

Gornale SS, Patravali PU, Manza RR. A survey on exploration and classification of osteoarthritis using image processing techniques. Int J Sci Eng Res. 2016;7(6):334–55.

Google Scholar 

Kokkotis C, Moustakidis S, Papageorgiou E, Giakas G, Tsaopoulos D. Machine learning in knee osteoarthritis: a review. Osteoar Cartil. 2020;2(3): 100069.

Article  Google Scholar 

Khalid H, Hussain M, Al Ghamdi MA, Khalid T, Khalid K, Khan MA, Fatima K, Masood K, Almotiri SH, Farooq MS, et al. A comparative systematic literature review on knee bone reports from mri, x-rays and ct scans using deep learning and machine learning methodologies. Diagnostics. 2020;10(8):518.

Article  MATH  Google Scholar 

Roemer FW, Guermazi A, Demehri S, Wirth W, Kijowski R. Imaging in osteoarthritis. Osteoarthritis and Cartilage; 2021.

Lee LS, Chan PK, Wen C, Fung WC, Cheung A, Chan VWK, Cheung MH, Fu H, Yan CH, Chiu KY. Artificial intelligence in diagnosis of knee osteoarthritis and prediction of arthroplasty outcomes: a review. Arthroplasty. 2022;4(1):16.

Article  MATH  Google Scholar 

Almhdie-Imjabbar A, Toumi H, Lespessailles E. Radiographic biomarkers for knee osteoarthritis: A narrative review. Life. 2023;13(1):237.

Article  Google Scholar 

Kijowski R, Fritz J, Deniz CM. Deep learning applications in osteoarthritis imaging. Skelet Radiol. 2023;52(11):2225–38.

Article  MATH  Google Scholar 

Xuan A, Chen H, Chen T, Li J, Lu S, Fan T, Zeng D, Wen Z, Ma J, Hunter D, et al. The application of machine learning in early diagnosis of osteoarthritis: a narrative review. Ther Adv Musculoskelet Dis. 2023;15:1759720–231158198.

Article  Google Scholar 

Yeoh PSQ, Lai KW, Goh SL, Hasikin K, Hum YC, Tee YK, Dhanalakshmi S. Emergence of deep learning in knee osteoarthritis diagnosis. Computational intelligence and neuroscience 2021; 2021.

Badshah Y, Shabbir M, Hayat H, Fatima Z, Burki A, Khan S, et al. Genetic markers of osteoarthritis: early diagnosis in susceptible pakistani population. J Orthop Surg Res. 2021;16(1):1–8.

Article  MATH  Google Scholar 

Yong CW, Teo K, Murphy BP, Hum YC, Tee YK, Xia K, Lai KW. Knee osteoarthritis severity classification with ordinal regression module. Multimedia Tools and Applications, 2021:1–13.

Tariq T, Suhail Z, Nawaz Z. Knee osteoarthritis detection and classification using x-rays. IEEE Access. 2023;11:48292–303. https://doi.org/10.1109/ACCESS.2023.3276810.

Article  Google Scholar 

Kellgren JH, Lawrence J. Radiological assessment of osteo-arthrosis. Ann Rheum Dis. 1957;16(4):494.

Article  MATH  Google Scholar 

Wright RW, Ross JR, Haas AK, Huston LJ, Garofoli EA, Harris D, Patel K, Pearson D, Schutzman J, Tarabichi M, et al. Osteoarthritis classification scales: interobserver reliability and arthroscopic correlation. J Bone Joint Surg Am. 2014;96(14):1145.

Article  Google Scholar 

Swagerty DL Jr, Hellinger D. Radiographic assessment of osteoarthritis. Am Fam Phys. 2001;64(2):279.

MATH  Google Scholar 

Scheller G, Sobau C, Bülow JU. Arthroscopic partial lateral meniscectomy in an otherwise normal knee: clinical, functional, and radiographic results of a long-term follow-up study. Arthrosc J Arthrosc Relat Surg. 2001;17(9):946–52.

Article  Google Scholar 

Culvenor AG, Engen CN, Øiestad BE, Engebretsen L, Risberg MA. Defining the presence of radiographic knee osteoarthritis: a comparison between the kellgren and lawrence system and oarsi atlas criteria. Knee Surg Sports Traumatol Arthrosc. 2015;23(12):3532–9.

Article  Google Scholar 

Wesseling J, Boers M, Viergever MA, Hilberdink WK, Lafeber FP, Dekker J, Bijlsma JW. Cohort profile: cohort hip and cohort knee (check) study. Int J Epidemiol. 2016;45(1):36–44.

Article  Google Scholar 

https://nda.nih.gov/oai

http://most.ucsf.edu/default.asp (2013)

Chen, P. Knee Osteoarthritis Severity Grading Dataset. https://doi.org/10.17632/56rmx5bjcr.1 . https://data.mendeley.com/datasets/56rmx5bjcr/1/

Shivanand Gornale PP. Digital Knee X-ray Images. Mendeley Data; 2020. https://doi.org/10.17632/t9ndx37v5h.1 . https://data.mendeley.com/datasets/t9ndx37v5h/1/

Olsson S, Akbarian E, Lind A, Razavian AS, Gordon M. Automating classification of osteoarthritis according to kellgren-lawrence in the knee using deep learning in an unfiltered adult population. BMC Musculoskelet Disord. 2021;22(1):1–8.

Article  Google Scholar 

Lester G. The osteoarthritis initiative: a nih public-private partnership. HSS J. 2012;8(1):62–3.

Article  MATH  Google Scholar 

Segal N, Nevitt M, Gross K, Hietpas J, Glass N, Lewis C, Torner J. The multicenter osteoarthritis study: opportunities for rehabilitation research (vol 8, pg 647, 2013). PM &R. 2013;5(11):987–987.

MATH  Google Scholar 

Brahim A, Riad R, Jennane R. Knee osteoarthritis detection using power spectral density: Data from the osteoarthritis initiative. In: International Conference on Computer Analysis of Images and Patterns, 2019:480–487. Springer

Gornale SS, Patravali PU, Hiremath PS. Automatic detection and classification of knee osteoarthritis using hu’s invariant moments. Frontiers in Robotics and AI, 2020;7.

Saleem M, Farid MS, Saleem S, Khan MH. X-ray image analysis for automated knee osteoarthritis detection. SIViP. 2020;14(6):1079–87.

Article  MATH  Google Scholar 

Wang K, Niu X, Dou Y, Xie D, Yang T. A siamese network with adaptive gated feature fusion for individual knee oa features grades prediction. Sci Rep. 2021;11(1):16833.

Article  Google Scholar 

Gonzalez RC. Digital Image Processing. Pearson education India ; 2009.

Ahmed SM, Mstafa RJ. Identifying severity grading of knee osteoarthritis from x-ray images using an efficient mixture of deep learning and machine learning models. Diagnostics. 2022;12(12):2939.

Article  MATH  Google Scholar 

Anifah L, Purnama IKE, Hariadi M, Purnomo MH. Osteoarthritis classification using self organizing map based on gabor kernel and contrast-limited adaptive histogram equalization. Open Biomed Eng J. 2013;7:18.

Article  Google Scholar 

Bayramoglu N, Tiulpin A, Hirvasniemi J, Nieminen MT, Saarakkala S. Adaptive segmentation of knee radiographs for selecting the optimal roi in texture analysis. Osteoarthr Cartil. 2020;28(7):941–52.

Article  Google Scholar 

Mahum R, Rehman SU, Meraj T, Rauf HT, Irtaza A, El-Sherbeeny AM, El-Meligy MA. A novel hybrid approach based on deep cnn features to detect knee osteoarthritis. Sensors. 2021;21(18):6189.

Article  Google Scholar 

Gornale SS, Patravali PU, Manza RR. Detection of osteoarthritis using knee x-ray image analyses: a machine vision based approach. Int J Comput Appl. 2016;145(1):0975–8887.

Google Scholar 

Antony J, McGuinness K, Moran K, O’Connor NE. Automatic detection of knee joints and quantification of knee osteoarthritis severity using convolutional neural networks. In: International Conference on Machine Learning and Data Mining in Pattern Recognition, 2017:376–390. Springer

Farajzadeh N, Sadeghzadeh N, Hashemzadeh M. Ijes-oa net: a residual neural network to classify knee osteoarthritis from radiographic imag