AIMC Topic: Radiography

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Current challenges of implementing artificial intelligence in medical imaging.

Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB) Jun 14, 2022
The idea of using artificial intelligence (AI) in medical practice has gained vast interest due to its potential to revolutionise healthcare systems. However, only some AI algorithms are utilised due to systems' uncertainties, besides the never-endin...
Algorithms Humans Radiography Artificial Intelligence Diagnostic Imaging Radiology
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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.
Deep Learning Magnetic Resonance Imaging Radiography Knee Joint Humans Femur Anterior Cruciate Ligament Injuries
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Automatic Cobb angle measurement method based on vertebra segmentation by deep learning.

Medical & biological engineering & computing Jun 9, 2022
The accuracy of the Cobb measurement is essential for the diagnosis and treatment of scoliosis. Manual measurement is however influenced by the observer variability hence affecting progression evaluation. In this paper, we propose a fully automatic C...
Radiography Spine Scoliosis Deep Learning Image Processing, Computer-Assisted Humans Algorithms
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Deep Learning Prediction of Survival in Patients with Chronic Obstructive Pulmonary Disease Using Chest Radiographs.

Radiology Jun 7, 2022
Background Preexisting indexes for predicting the prognosis of chronic obstructive pulmonary disease (COPD) do not use radiologic information and are impractical because they involve complex history assessments or exercise tests. Purpose To develop a...
Deep Learning Radiography Retrospective Studies Pulmonary Disease, Chronic Obstructive Forced Expiratory Volume Respiratory Function Tests Humans
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Unsupervised Cross-Modality Domain Adaptation Network for X-Ray to CT Registration.

IEEE journal of biomedical and health informatics Jun 3, 2022
2D/3D registration that achieves high accuracy and real-time computation is one of the enabling technologies for radiotherapy and image-guided surgeries. Recently, the Convolutional Neural Network (CNN) has been explored to significantly improve the ...
Humans Neural Networks, Computer Radiography X-Rays Tomography, X-Ray Computed Image Processing, Computer-Assisted
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Towards fully automated segmentation of rat cardiac MRI by leveraging deep learning frameworks.

Scientific reports Jun 2, 2022
Automated segmentation of human cardiac magnetic resonance datasets has been steadily improving during recent years. Similar applications would be highly useful to improve and speed up the studies of cardiac function in rodents in the preclinical con...
Animals Deep Learning Heart Ventricles Rats Radiography Magnetic Resonance Imaging Heart
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Improving Medical Images Classification With Label Noise Using Dual-Uncertainty Estimation.

IEEE transactions on medical imaging Jun 1, 2022
Deep neural networks are known to be data-driven and label noise can have a marked impact on model performance. Recent studies have shown great robustness to classic image recognition even under a high noisy rate. In medical applications, learning fr...
Neural Networks, Computer Diagnostic Imaging Noise Uncertainty Radiography
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ThoraciNet: thoracic abnormality detection and disease classification using fusion DCNNs.

Physical and engineering sciences in medicine May 30, 2022
Chest X-rays are arguably the de facto medical imaging technique for diagnosing thoracic abnormalities. Chest X-ray analysis is complex, especially in asymptomatic diseases, and relies heavily on the expertise of radiologists. This work proposes the ...
Radiography Humans Neural Networks, Computer Radiography, Thoracic Databases, Factual Diagnosis, Computer-Assisted
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A novel approach to radiographic detection of growth development period with hand-wrist radiographs: A preliminary study with ImageJ imaging software.

Orthodontics & craniofacial research May 20, 2022
OBJECTIVE: The purpose of this study is to determine whether or not the ImageJ program can be used to automatically determine the growth period of the hand and wrist which have different growth-development periods according to the density values in t...
Age Determination by Skeleton Wrist Hand Software Radiography Humans Artificial Intelligence
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Deep Learning and Imaging for the Orthopaedic Surgeon: How Machines "Read" Radiographs.

The Journal of bone and joint surgery. American volume May 20, 2022
➤: In the not-so-distant future, orthopaedic surgeons will be exposed to machines that begin to automatically "read" medical imaging studies using a technology called deep learning.
Radiography Deep Learning Humans Orthopedic Surgeons Tomography, X-Ray Computed Magnetic Resonance Imaging
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