AIMC Topic: Radiography

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A Conference-Friendly, Hands-on Introduction to Deep Learning for Radiology Trainees.

Journal of digital imaging Jul 29, 2021
Artificial or augmented intelligence, machine learning, and deep learning will be an increasingly important part of clinical practice for the next generation of radiologists. It is therefore critical that radiology residents develop a practical under...
Radiology Radiologists Deep Learning Humans Radiography Machine Learning
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LPAQR-Net: Efficient Vertebra Segmentation From Biplanar Whole-Spine Radiographs.

IEEE journal of biomedical and health informatics Jul 27, 2021
Vertebra segmentation from biplanar whole-spine radiographs is highly demanded in the quantitative assessment of scoliosis and the resultant sagittal deformities. However, automatic vertebra segmentation from the radiographs is extremely challenging ...
Humans Neural Networks, Computer Radiography Spine Tomography, X-Ray Computed Image Processing, Computer-Assisted
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Deep learning to automate the labelling of head MRI datasets for computer vision applications.

European radiology Jul 20, 2021
OBJECTIVES: The purpose of this study was to build a deep learning model to derive labels from neuroradiology reports and assign these to the corresponding examinations, overcoming a bottleneck to computer vision model development.
Radiography Radiologists Magnetic Resonance Imaging Humans Area Under Curve Deep Learning
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AI MSK clinical applications: spine imaging.

Skeletal radiology Jul 15, 2021
Recent investigations have focused on the clinical application of artificial intelligence (AI) for tasks specifically addressing the musculoskeletal imaging routine. Several AI applications have been dedicated to optimizing the radiology value chain ...
Forecasting Radiography Humans Diagnostic Imaging Artificial Intelligence Radiology
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A deep learning approach to automatically quantify lower extremity alignment in children.

Skeletal radiology Jul 13, 2021
OBJECTIVE: To develop and validate a convolutional neural network (CNN) capable of predicting the anatomical landmarks used to calculate the hip-knee-ankle angles (HKAAs) from radiographs and thereby quantify lower extremity alignments in children.
Radiography Tibia Child Lower Extremity Deep Learning Adolescent Humans Neural Networks, Computer
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Development and web deployment of an automated neuroradiology MRI protocoling tool with natural language processing.

BMC medical informatics and decision making Jul 12, 2021
BACKGROUND: A systematic approach to MRI protocol assignment is essential for the efficient delivery of safe patient care. Advances in natural language processing (NLP) allow for the development of accurate automated protocol assignment. We aim to de...
Radiology Workflow Natural Language Processing Radiography Humans Magnetic Resonance Imaging
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Clinical applicability of automated cephalometric landmark identification: Part II - Number of images needed to re-learn various quality of images.

Orthodontics & craniofacial research Jul 11, 2021
AIM: To estimate the number of cephalograms needed to re-learn for different quality images, when artificial intelligence (AI) systems are introduced in a clinic.
Radiography Cephalometry Humans Artificial Intelligence
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Automatic Prediction of Recurrence of Major Cardiovascular Events: A Text Mining Study Using Chest X-Ray Reports.

Journal of healthcare engineering Jul 9, 2021
METHODS: We used EHR data of patients included in the Second Manifestations of ARTerial disease (SMART) study. We propose a deep learning-based multimodal architecture for our text mining pipeline that integrates neural text representation with prepr...
Data Mining Humans Cardiovascular Diseases X-Rays Radiography Neural Networks, Computer
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Automated detection of patellofemoral osteoarthritis from knee lateral view radiographs using deep learning: data from the Multicenter Osteoarthritis Study (MOST).

Osteoarthritis and cartilage Jul 8, 2021
OBJECTIVE: To assess the ability of imaging-based deep learning to detect radiographic patellofemoral osteoarthritis (PFOA) from knee lateral view radiographs.
Aged Male Humans Female Osteoarthritis, Knee Patellofemoral Joint Radiography Datasets as Topic Middle Aged Deep Learning
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Understanding artificial intelligence based radiology studies: CNN architecture.

Clinical imaging Jul 7, 2021
Artificial intelligence (AI) in radiology has gained wide interest due to the development of neural network architectures with high performance in computer vision related tasks. As AI based software programs become more integrated into the clinical w...
Radiologists Workflow Radiography Humans Radiology Artificial Intelligence
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