AIMC Topic: Femur

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Inferring the locomotor ecology of two of the oldest fossil squirrels: influence of operationalization, trait, body size and machine learning method.

Proceedings. Biological sciences
Correlations between morphology and lifestyle of extant taxa are useful for predicting lifestyles of extinct relatives. Here, we infer the locomotor behaviour of from the middle Oligocene and from the lower Miocene of France using their femoral mor...

Better Rough Than Scarce: Proximal Femur Fracture Segmentation With Rough Annotations.

IEEE transactions on medical imaging
Proximal femoral fracture segmentation in computed tomography (CT) is essential in the preoperative planning of orthopedic surgeons. Recently, numerous deep learning-based approaches have been proposed for segmenting various structures within CT scan...

Development of an artificial intelligence model for predicting implant size in total knee arthroplasty using simple X-ray images.

Journal of orthopaedic surgery and research
BACKGROUND: Accurate estimation of implant size before surgery is crucial in preparing for total knee arthroplasty. However, this task is time-consuming and labor-intensive. To alleviate this burden on surgeons, we developed a reliable artificial int...

Explainable machine-learning-based prediction of QCT/FEA-calculated femoral strength under stance loading configuration using radiomics features.

Journal of orthopaedic research : official publication of the Orthopaedic Research Society
Finite element analysis can provide precise femoral strength assessment. However, its modeling procedures were complex and time-consuming. This study aimed to develop a model to evaluate femoral strength calculated by quantitative computed tomography...

Artificial intelligence-based assessment of leg axis parameters shows excellent agreement with human raters: A systematic review and meta-analysis.

Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
PURPOSE: The aim of this study was to conduct a systematic review and meta-analysis on the reliability and applicability of artificial intelligence (AI)-based analysis of leg axis parameters. We hypothesized that AI-based leg axis measurements would ...

Finite element models with automatic computed tomography bone segmentation for failure load computation.

Scientific reports
Bone segmentation is an important step to perform biomechanical failure load simulations on in-vivo CT data of patients with bone metastasis, as it is a mandatory operation to obtain meshes needed for numerical simulations. Segmentation can be a tedi...

Deep learning-based quantification of osteonecrosis using magnetic resonance images in Gaucher disease.

Bone
Gaucher disease is one of the most common lysosomal storage disorders. Osteonecrosis is a principal clinical manifestation of Gaucher disease and often leads to joint collapse and fractures. T1-weighted (T1w) modality in MRI is widely used to monitor...

Three-dimensional magnetic resonance imaging-based statistical shape analysis and machine learning-based prediction of patellofemoral instability.

Scientific reports
This study performed three-dimensional (3D) magnetic resonance imaging (MRI)-based statistical shape analysis (SSA) by comparing patellofemoral instability (PFI) and normal femur models, and developed a machine learning (ML)-based prediction model. T...

Automatic segmentation of femoral tumors by nnU-net.

Clinical biomechanics (Bristol, Avon)
BACKGROUND: Metastatic femoral tumors may lead to pathological fractures during daily activities. A CT-based finite element analysis of a patient's femurs was shown to assist orthopedic surgeons in making informed decisions about the risk of fracture...