Search Results - "Skeletal radiology"
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Detecting intertrochanteric hip fractures with orthopedist-level accuracy using a deep convolutional neural network
Published in Skeletal radiology (01-02-2019)“…Objective To compare performances in diagnosing intertrochanteric hip fractures from proximal femoral radiographs between a convolutional neural network and…”
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2
A comparison of ChatGPT-generated articles with human-written articles
Published in Skeletal radiology (01-09-2023)“…Objective ChatGPT (Generative Pre-trained Transformer) is an artificial intelligence language tool developed by OpenAI that utilises machine learning…”
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3
Shear wave sonoelastography of skeletal muscle: basic principles, biomechanical concepts, clinical applications, and future perspectives
Published in Skeletal radiology (01-04-2018)“…Imaging plays an important role in the diagnosis and therapeutic response evaluation of muscular diseases. However, one important limitation is its incapacity…”
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4
Musculoskeletal involvement of COVID-19: review of imaging
Published in Skeletal radiology (01-09-2021)“…The global pandemic of coronavirus disease 2019 (COVID-19) has revealed a surprising number of extra-pulmonary manifestations of severe acute respiratory…”
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5
Comparison of PSMA-PET/CT, choline-PET/CT, NaF-PET/CT, MRI, and bone scintigraphy in the diagnosis of bone metastases in patients with prostate cancer: a systematic review and meta-analysis
Published in Skeletal radiology (01-12-2019)“…Objective A systematic review and meta-analysis to compare the diagnostic performance of prostate-specific membrane antigen (PSMA)-PET/CT, choline-PET/CT,…”
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6
Comparison of choline-PET/CT, MRI, SPECT, and bone scintigraphy in the diagnosis of bone metastases in patients with prostate cancer: a meta-analysis
Published in Skeletal radiology (01-11-2014)“…Published data on the diagnosis of bone metastases of prostate cancer are conflicting and heterogeneous. We performed a comprehensive meta-analysis to compare…”
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7
Adhesive capsulitis: review of imaging findings, pathophysiology, clinical presentation, and treatment options
Published in Skeletal radiology (01-08-2019)“…Adhesive capsulitis, commonly referred to as “frozen shoulder,” is a debilitating condition characterized by progressive pain and limited range of motion about…”
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Current applications and future directions of deep learning in musculoskeletal radiology
Published in Skeletal radiology (01-02-2020)“…Deep learning with convolutional neural networks (CNN) is a rapidly advancing subset of artificial intelligence that is ideally suited to solving image-based…”
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Subacromial-subdeltoid bursitis following COVID-19 vaccination: a case of shoulder injury related to vaccine administration (SIRVA)
Published in Skeletal radiology (01-11-2021)“…Vaccination injection site adverse reactions are usually mild and transient, and post-vaccination musculoskeletal symptoms, such as myalgia and arthralgia, are…”
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10
MRI nomenclature for musculoskeletal infection
Published in Skeletal radiology (01-12-2021)“…The Society of Skeletal Radiology (SSR) Practice Guidelines and Technical Standards Committee identified musculoskeletal infection as a White Paper topic, and…”
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11
Improved visualization of the wrist at lower radiation dose with photon-counting-detector CT
Published in Skeletal radiology (2023)“…Objective To compare the image quality of ultra-high-resolution wrist CTs acquired on photon-counting detector CT versus conventional…”
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12
Deep learning for automated segmentation of pelvic muscles, fat, and bone from CT studies for body composition assessment
Published in Skeletal radiology (01-03-2020)“…Objective To develop a deep convolutional neural network (CNN) to automatically segment an axial CT image of the pelvis for body composition measures. We…”
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13
MRI appearance of the different meniscal ramp lesion types, with clinical and arthroscopic correlation
Published in Skeletal radiology (01-05-2020)“…Background Meniscal ramp lesions have been defined as longitudinal vertical peripheral tears of the medial meniscus involving the posterior meniscocapsular…”
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14
Deep learning approach to predict pain progression in knee osteoarthritis
Published in Skeletal radiology (01-02-2022)“…Objective To develop and evaluate deep learning (DL) risk assessment models for predicting pain progression in subjects with or at risk of knee osteoarthritis…”
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15
Current status and recommendations for imaging in neurofibromatosis type 1, neurofibromatosis type 2, and schwannomatosis
Published in Skeletal radiology (01-02-2020)“…Neurofibromatosis type 1 (NF1), neurofibromatosis type 2 (NF2), and schwannomatosis (SWN) are three clinically distinct tumor predisposition syndromes with a…”
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16
Artificial intelligence-assisted interpretation of bone age radiographs improves accuracy and decreases variability
Published in Skeletal radiology (01-02-2019)“…Objective Radiographic bone age assessment (BAA) is used in the evaluation of pediatric endocrine and metabolic disorders. We previously developed an automated…”
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17
Radiologic evaluation of fracture healing
Published in Skeletal radiology (01-03-2019)“…While assessment of fracture healing is a common task for both orthopedic surgeons and radiologists, it remains challenging due to a lack of consensus on…”
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18
Fully automated deep learning for knee alignment assessment in lower extremity radiographs: a cross-sectional diagnostic study
Published in Skeletal radiology (01-06-2022)“…Objectives Accurate assessment of knee alignment and leg length discrepancy is currently measured manually from standing long-leg radiographs (LLR), a process…”
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19
Glossary of terms for musculoskeletal radiology
Published in Skeletal radiology (01-07-2020)“…Members of the International Skeletal Society compiled a glossary of terms for musculoskeletal radiology. The authors also represent national radiology or…”
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Imaging in syndesmotic injury: a systematic literature review
Published in Skeletal radiology (01-05-2018)“…Objectives To give a systematic overview of current diagnostic imaging options for assessment of the distal tibio-fibular syndesmosis. Materials and methods A…”
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