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Cartilage

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Cartilage structure increases swimming efficiency of underwater robots.

Scientific reports
Underwater robots are useful for exploring valuable resources and marine life. Traditional underwater robots use screw propellers, which may be harmful to marine life. In contrast, robots that incorporate the swimming principles, morphologies, and so...

[Segmentation of knee cartilages in MR images with artificial intelligence].

Orvosi hetilap
UNLABELLED: Összefoglaló. Bevezetés: A térdízületnek ultrafriss osteochondralis allograft segítségével történő részleges ortopédiai rekonstrukciója képalkotó vizsgálatokon alapuló pontos tervezést igényel, mely folyamatban a morfológia felismerésére ...

Deep Learning for US Image Quality Assessment Based on Femoral Cartilage Boundary Detection in Autonomous Knee Arthroscopy.

IEEE transactions on ultrasonics, ferroelectrics, and frequency control
Knee arthroscopy is a complex minimally invasive surgery that can cause unintended injuries to femoral cartilage or postoperative complications, or both. Autonomous robotic systems using real-time volumetric ultrasound (US) imaging guidance hold pote...

Machine learning to predict mesenchymal stem cell efficacy for cartilage repair.

PLoS computational biology
Inconsistent therapeutic efficacy of mesenchymal stem cells (MSCs) in regenerative medicine has been documented in many clinical trials. Precise prediction on the therapeutic outcome of a MSC therapy based on the patient's conditions would provide va...

Deep learning-based fully automatic segmentation of wrist cartilage in MR images.

NMR in biomedicine
The study objective was to investigate the performance of a dedicated convolutional neural network (CNN) optimized for wrist cartilage segmentation from 2D MR images. CNN utilized a planar architecture and patch-based (PB) training approach that ensu...

Multi-classifier prediction of knee osteoarthritis progression from incomplete imbalanced longitudinal data.

Scientific reports
Conventional inclusion criteria used in osteoarthritis clinical trials are not very effective in selecting patients who would benefit from a therapy being tested. Typically majority of selected patients show no or limited disease progression during a...

Super-resolution reconstruction of knee magnetic resonance imaging based on deep learning.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVE: With the rapid development of medical imaging and intelligent diagnosis, artificial intelligence methods have become a research hotspot of radiography processing technology in recent years. The low definition of knee magneti...

Incorporating prior knowledge via volumetric deep residual network to optimize the reconstruction of sparsely sampled MRI.

Magnetic resonance imaging
For sparse sampling that accelerates magnetic resonance (MR) image acquisition, non-linear reconstruction algorithms have been developed, which incorporated patient specific a prior information. More generic a prior information could be acquired via ...

Deep convolutional neural network for segmentation of knee joint anatomy.

Magnetic resonance in medicine
PURPOSE: To describe and evaluate a new segmentation method using deep convolutional neural network (CNN), 3D fully connected conditional random field (CRF), and 3D simplex deformable modeling to improve the efficiency and accuracy of knee joint tiss...