Nov 29, 2021 · This study deals with knee osteoarthritis X-ray images for disease detection purpose. As the disease severity increases, the knee joint space ...
The objective of this research is to present an approach by leveraging an ensemble of CNN models, specifically. MobileNet, ResNet, and AlexNet architectures.
May 24, 2020 · We propose a fully automated novel method, based on combination of joint shape and convolutional neural network (CNN) based bone texture features.
This study deals with knee osteoarthritis X-ray images for disease detection purpose. As the disease severity increases, the knee joint space gets reduced and ...
This paper suggests a method with higher predictive accuracy that can be employed in the real world for the early detection of knee osteoarthritis.
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Jul 8, 2020 · We propose a model that combines bone shape and bone texture using a tiny CNN model to detect OA. ... knee osteoarthritis detected by radiography.
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Sep 27, 2024 · Train the CNN model on the knee osteoarthritis dataset for 100 epochs. • Use a 90-10 training-validation split to monitor overfitting.
Sep 15, 2021 · A fully automated segmentation technique is used. This technique uses MR images and is applied for the detection of osteoarthritis of the knee ...
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Objective The purposes of this study were to investigate: 1) the effect of placement of region-of-interest (ROI) for texture analysis of subchondral bone in ...
This study utilizes a 3D CNN model to analyze sequences of knee magnetic resonance (MR) images to perform knee OA classification.
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