Deep learning-based medical images segmentation of musculoskeletal anatomical structures: a survey of bottlenecks and strategies
L Bonaldi, A Pretto, C Pirri, F Uccheddu, CG Fontanella… - Bioengineering, 2023 - mdpi.com
By leveraging the recent development of artificial intelligence algorithms, several medical
sectors have benefited from using automatic segmentation tools from bioimaging to segment …
sectors have benefited from using automatic segmentation tools from bioimaging to segment …
Technological advancements and elucidation gadgets for Healthcare applications: An exhaustive methodological review-part-I (AI, big data, block chain, open-source …
In the realm of the emergence and spread of infectious diseases with pandemic potential
throughout the history, plenty of pandemics (and epidemics), from the plague to AIDS (1981) …
throughout the history, plenty of pandemics (and epidemics), from the plague to AIDS (1981) …
The KNee OsteoArthritis Prediction (KNOAP2020) challenge: An image analysis challenge to predict incident symptomatic radiographic knee osteoarthritis from MRI …
J Hirvasniemi, J Runhaar, RA van der Heijden… - Osteoarthritis and …, 2023 - Elsevier
Summary Objectives The KNee OsteoArthritis Prediction (KNOAP2020) challenge was
organized to objectively compare methods for the prediction of incident symptomatic …
organized to objectively compare methods for the prediction of incident symptomatic …
Automated prediction of osteoarthritis level in human osteochondral tissue using histopathological images
Osteoarthritis (OA) is the most common arthritis and the leading cause of lower extremity
disability in older adults. Understanding OA progression is important in the development of …
disability in older adults. Understanding OA progression is important in the development of …
Deep learning applications in osteoarthritis imaging
Deep learning (DL) is one of the most exciting new areas in medical imaging. This article will
provide a review of current applications of DL in osteoarthritis (OA) imaging, including …
provide a review of current applications of DL in osteoarthritis (OA) imaging, including …
CartiMorph: A framework for automated knee articular cartilage morphometrics
We introduce CartiMorph, a framework for automated knee articular cartilage
morphometrics. It takes an image as input and generates quantitative metrics for cartilage …
morphometrics. It takes an image as input and generates quantitative metrics for cartilage …
A Convolution Neural Network Design for Knee Osteoarthritis Diagnosis Using X-ray Images.
SH Sajaan Almansour, R Singh… - … Journal of Online & …, 2023 - search.ebscohost.com
Knee osteoarthritis (OA) is a chronic degenerative joint disease affecting millions worldwide,
particularly those over 60. It is a significant cause of disability and can impact an individual's …
particularly those over 60. It is a significant cause of disability and can impact an individual's …
Osteoarthritis year in review 2023: Imaging
Purpose This narrative review summarizes the original research in the field of in vivo
osteoarthritis (OA) imaging between 1 January 2022 and 1 April 2023. Methods A PubMed …
osteoarthritis (OA) imaging between 1 January 2022 and 1 April 2023. Methods A PubMed …
[HTML][HTML] Predicting total knee arthroplasty from ultrasonography using machine learning
Objective To investigate the value of ultrasonographic data in predicting total knee
replacement (TKR). Design Data from the Musculoskeletal Pain in Ullensaker study (MUST) …
replacement (TKR). Design Data from the Musculoskeletal Pain in Ullensaker study (MUST) …
A novel multi-atlas segmentation approach under the semi-supervised learning framework: Application to knee cartilage segmentation
Background and objective: Multi-atlas based segmentation techniques, which rely on an
atlas library comprised of training images labeled by an expert, have proven their …
atlas library comprised of training images labeled by an expert, have proven their …