U-net and its variants for medical image segmentation: A review of theory and applications

N Siddique, S Paheding, CP Elkin… - IEEE access, 2021 - ieeexplore.ieee.org
U-net is an image segmentation technique developed primarily for image segmentation
tasks. These traits provide U-net with a high utility within the medical imaging community …

Studying osteoarthritis with artificial intelligence applied to magnetic resonance imaging

F Calivà, NK Namiri, M Dubreuil, V Pedoia… - Nature Reviews …, 2022 - nature.com
The 3D nature and soft-tissue contrast of MRI makes it an invaluable tool for osteoarthritis
research, by facilitating the elucidation of disease pathogenesis and progression. The recent …

Automatic MRI-based three-dimensional models of hip cartilage provide improved morphologic and biochemical analysis

F Schmaranzer, R Helfenstein, G Zeng… - Clinical Orthopaedics …, 2019 - journals.lww.com
Background The time-consuming and user-dependent postprocessing of biochemical
cartilage MRI has limited the use of delayed gadolinium-enhanced MRI of cartilage …

Fair AI-powered orthopedic image segmentation: addressing bias and promoting equitable healthcare

IA Siddiqui, N Littlefield, LA Carlson, M Gong… - Scientific Reports, 2024 - nature.com
AI-powered segmentation of hip and knee bony anatomy has revolutionized orthopedics,
transforming pre-operative planning and post-operative assessment. Despite the …

Semantic segmentation of the multiform proximal femur and femoral head bones with the deep convolutional neural networks in low quality MRI sections acquired in …

A Memiş, S Varlı, F Bilgili - Computerized Medical Imaging and Graphics, 2020 - Elsevier
Medical image segmentation is one of the most crucial issues in medical image processing
and analysis. In general, segmentation of the various structures in medical images is …

[HTML][HTML] MRI-based 3D models of the hip joint enables radiation-free computer-assisted planning of periacetabular osteotomy for treatment of hip dysplasia using deep …

G Zeng, F Schmaranzer, C Degonda, N Gerber… - European journal of …, 2021 - Elsevier
Abstract Introduction Both Hip Dysplasia (DDH) and Femoro-acetabular-Im**ement (FAI)
are complex three-dimensional hip pathologies causing hip pain and osteoarthritis in young …

LatentPCN: latent space-constrained point cloud network for reconstruction of 3D patient-specific bone surface models from calibrated biplanar X-ray images

W Sun, Y Zhao, J Liu, G Zheng - International Journal of Computer …, 2023 - Springer
Purpose Accurate three-dimensional (3D) models play crucial roles in computer assisted
planning and interventions. MR or CT images are frequently used to derive 3D models but …

Deep 3D convolutional networks to segment bones affected by severe osteoarthritis in CT scans for PSI-based knee surgical planning

D Marzorati, M Sarti, L Mainardi, A Manzotti… - IEEE …, 2020 - ieeexplore.ieee.org
Segmentation of bony structures in CT scans is a crucial step in knee arthroplasty based on
personalized surgical instruments (PSI). As a matter of fact, the success of the surgery …

MRI‐and CT‐based metrics for the quantification of arthroscopic bone resections in femoroacetabular im**ement syndrome

M Guidetti, P Malloy, TD Alter… - Journal of …, 2022 - Wiley Online Library
The purpose of this in vitro study was to quantify the bone resected from the proximal femur
during hip arthroscopy using metrics generated from magnetic resonance imaging (MRI) …

Better Rough than Scarce: Proximal Femur Fracture Segmentation with Rough Annotations

X Lu, Z Cui, Y Sun, HG Khor, A Sun… - … on Medical Imaging, 2024 - ieeexplore.ieee.org
Proximal femoral fracture segmentation in computed tomography (CT) is essential in the
preoperative planning of orthopedic surgeons. Recently, numerous deep learning-based …