AIMC Topic: Femur
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Auto-segmentation of the tibia and femur from knee MR images via deep learning and its application to cartilage strain and recovery.
Journal of biomechanics
Jan 26, 2023
The ability to efficiently and reproducibly generate subject-specific 3D models of bone and soft tissue is important to many areas of musculoskeletal research. However, methodologies requiring such models have largely been limited by lengthy manual s...
Stature estimation by semi-automatic measurements of 3D CT images of the femur.
International journal of legal medicine
Dec 7, 2022
Stature estimation is one of the most basic and important methods of personal identification. The long bones of the limbs provide the most accurate stature estimation, with the femur being one of the most useful. In all the previously reported method...
Radiographic findings involved in knee osteoarthritis progression are associated with pain symptom frequency and baseline disease severity: a population-level analysis using deep learning.
Knee surgery, sports traumatology, arthroscopy : official journal of the ESSKA
Nov 11, 2022
PURPOSE: To (1) develop a deep-learning (DL) algorithm capable of producing limb-length and knee-alignment measurements, and (2) determine the association between limb-length discrepancy (LLD), coronal-plane alignment, osteoarthritis (OA) severity, a...
Femoral image segmentation based on two-stage convolutional network using 3D-DMFNet and 3D-ResUnet.
Computer methods and programs in biomedicine
Sep 6, 2022
OBJECTIVE: The femur is a typical human long bone with an irregular spatial structure. Femoral fractures are the most common occurrence in middle-aged and older adults. The structure of human bone tissue is very complex, and there are significant dif...
Ensemble deep learning model for predicting anterior cruciate ligament tear from lateral knee radiograph.
Skeletal radiology
Jun 9, 2022
OBJECTIVE: To develop an ensemble deep learning model (DLM) predicting anterior cruciate ligament (ACL) tears from lateral knee radiographs and to evaluate its diagnostic performance.
Automatic segmentation model of intercondylar fossa based on deep learning: a novel and effective assessment method for the notch volume.
BMC musculoskeletal disorders
May 6, 2022
BACKGROUND: Notch volume is associated with anterior cruciate ligament (ACL) injury. Manual tracking of intercondylar notch on MR images is time-consuming and laborious. Deep learning has become a powerful tool for processing medical images. This stu...
Vision Transformer for femur fracture classification.
Injury
Apr 19, 2022
INTRODUCTION: In recent years, the scientific community focused on developing Computer-Aided Diagnosis (CAD) tools that could improve clinicians' bone fractures diagnosis, primarily based on Convolutional Neural Networks (CNNs). However, the discerni...
A morphometric analysis of the osteocyte canaliculus using applied automatic semantic segmentation by machine learning.
Journal of bone and mineral metabolism
Mar 26, 2022
INTRODUCTION: Osteocytes play a role as mechanosensory cells by sensing flow-induced mechanical stimuli applied on their cell processes. High-resolution imaging of osteocyte processes and the canalicular wall are necessary for the analysis of this me...
A deep learning-based approach to automatic proximal femur segmentation in quantitative CT images.
Medical & biological engineering & computing
Mar 24, 2022
Automatic CT segmentation of proximal femur has a great potential for use in orthopedic diseases, especially in the imaging-based assessments of hip fracture risk. In this study, we proposed an approach based on deep learning for the fast and automat...
A fully automated sex estimation for proximal femur X-ray images through deep learning detection and classification.
Legal medicine (Tokyo, Japan)
Mar 23, 2022
PURPOSE: To develop a fully automated deep learning pipeline using digital radiographs to detect the proximal femur region for accurate automated sex estimation.
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