AIMC Topic: Femur

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Deep learning based classification of tibio-femoral knee osteoarthritis from lateral view knee joint X-ray images.

Scientific reports
Design an effective deep learning-driven method to locate and classify the tibio-femoral knee joint space width (JSW) with respect to both anterior-posterior (AP) and lateral views. Compare the results and see how successfully a deep learning approac...

Fully automated workflow for designing patient-specific orthopaedic implants: Application to total knee arthroplasty.

PloS one
Background Osteoarthritis affects about 528 million people worldwide, causing pain and stiffness in the joints. Arthroplasty is commonly performed to treat joint osteoarthritis, reducing pain and improving mobility. Nevertheless, a significant share ...

Deep learning-aided segmentation combined with finite element analysis reveals a more natural biomechanic of dinosaur fossil.

Scientific reports
Finite element analysis (FEA), a biomechanical simulation technique capable of providing direct mechanical visualization for CT-based digital models, has been extensively applied to fossil image datasets to address key evolutionary questions in paleo...

Automated opportunistic screening for osteoporosis using deep learning-based automatic segmentation and radiomics on proximal femur images from low-dose abdominal CT.

BMC musculoskeletal disorders
RATIONALE AND OBJECTIVES: To establish an automated osteoporosis detection model based on low-dose abdominal CT (LDCT). This model combined a deep learning-based automatic segmentation of the proximal femur with a radiomics-based bone status classifi...

A Two stage deep learning network for automated femoral segmentation in bilateral lower limb CT scans.

Scientific reports
This study presents the development of a deep learning-based two-stage network designed for the efficient and precise segmentation of the femur in full lower limb CT images. The proposed network incorporates a dual-phase approach: rapid delineation o...

ShapeMed-Knee: A Dataset and Neural Shape Model Benchmark for Modeling 3D Femurs.

IEEE transactions on medical imaging
Analyzing anatomic shapes of tissues and organs is pivotal for accurate disease diagnostics and clinical decision-making. One prominent disease that depends on anatomic shape analysis is osteoarthritis, which affects 30 million Americans. To advance ...

Bone-wise rigid registration of femur, tibia, and fibula for the tracking of temporal changes.

Journal of applied clinical medical physics
BACKGROUND: Multiple myeloma (MM) induces temporal alterations in bone structure, such as osteolytic bone lesions, which are challenging to identify through manual image interpretation. The large variation in radiologists' assessments, even at expert...

A deep learning and statistical shape modeling-based method for assessing intercondylar notch volume in anterior cruciate ligament reconstruction.

The Knee
BACKGROUND: Anterior cruciate ligament (ACL) reconstruction is a widely performed procedure for ACL injury, but there are several factors which may lead to re-rupture or clinical failure. An intercondylar notch (or fossa) that is narrower may increas...

Leveraging deep learning for nonlinear shape representation in anatomically parameterized statistical shape models.

International journal of computer assisted radiology and surgery
PURPOSE: Statistical shape models (SSMs) are widely used for morphological assessment of anatomical structures. However, a key limitation is the need for a clear relationship between the model's shape coefficients and clinically relevant anatomical p...

Novel dilation-erosion labeling technique allows for rapid, accurate and adjustable alignment measurements in primary TKA.

Computers in biology and medicine
BACKGROUND: Optimal implant position and alignment remains a controversial, yet critical topic in primary total knee arthroplasty (TKA). Future study of ideal implant position will require the ability to efficiently measure component positions at sca...