AIMC Topic: Radiography

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Editorial for "Breast MRI Background Parenchymal Enhancement Categorization Using Deep Learning: Outperforming the Radiologist".

Journal of magnetic resonance imaging : JMRI Mar 28, 2022
Deep Learning Female Breast Neoplasms Magnetic Resonance Imaging Radiography Humans Retrospective Studies Radiologists Breast
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Measuring the critical shoulder angle on radiographs: an accurate and repeatable deep learning model.

Skeletal radiology Mar 28, 2022
PURPOSE: Since the critical shoulder angle (CSA) is considered a risk factor for shoulder pathology and the intra- and inter-rater variabilities in its calculation are not negligible, we developed a deep learning model that calculates it automaticall...
Shoulder Joint Radiography Shoulder Humans Retrospective Studies Deep Learning
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Diagnosis of osteoarthritic changes, loss of cervical lordosis, and disc space narrowing on cervical radiographs with deep learning methods.

Joint diseases and related surgery Mar 28, 2022
OBJECTIVES: In this study, we aimed to differentiate normal cervical graphs and graphs of diseases that cause mechanical neck pain by using deep convolutional neural networks (DCNN) technology.
Intervertebral Disc Degeneration Deep Learning Lordosis Radiography Humans Retrospective Studies
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Deep Learning Classification of Spinal Osteoporotic Compression Fractures on Radiographs using an Adaptation of the Genant Semiquantitative Criteria.

Academic radiology Mar 26, 2022
RATIONALE AND OBJECTIVES: Osteoporosis affects 9% of individuals over 50 in the United States and 200 million women globally. Spinal osteoporotic compression fractures (OCFs), an osteoporosis biomarker, are often incidental and under-reported. Accura...
Deep Learning Humans Radiography Osteoporosis Female Spinal Fractures Fractures, Compression Male
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Diagnostic accuracy of a commercially available deep-learning algorithm in supine chest radiographs following trauma.

The British journal of radiology Mar 24, 2022
OBJECTIVES: Trauma chest radiographs may contain subtle and time-critical pathology. Artificial intelligence (AI) may aid in accurate reporting, timely identification and worklist prioritisation. However, few AI programs have been externally validate...
Radiography, Thoracic Deep Learning Retrospective Studies Radiography Artificial Intelligence Male Humans Aged Algorithms Adult Middle Aged
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A ensemble methodology for automatic classification of chest X-rays using deep learning.

Computers in biology and medicine Mar 23, 2022
Chest radiographies, or chest X-rays, are the most standard imaging exams used in daily hospitals. Responsible for assisting in detecting numerous pathologies and findings that directly interfere in the patient's life, this exam is therefore crucial ...
Neural Networks, Computer Deep Learning Radiography X-Rays Humans
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Method to Minimize the Errors of AI: Quantifying and Exploiting Uncertainty of Deep Learning in Brain Tumor Segmentation.

Sensors (Basel, Switzerland) Mar 21, 2022
Despite the unprecedented success of deep learning in various fields, it has been recognized that clinical diagnosis requires extra caution when applying recent deep learning techniques because false prediction can result in severe consequences. In t...
Uncertainty Humans Deep Learning Brain Neoplasms Radiography
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Learning-based occupational x-ray scatter estimation.

Physics in medicine and biology Mar 21, 2022
During x-ray-guided interventional procedures, the medical staff is exposed to scattered ionizing radiation caused by the patient. To increase the staff's awareness of the invisible radiation and monitor dose online, computational scatter estimation ...
Humans Neural Networks, Computer Monte Carlo Method X-Rays Radiography Radiation, Ionizing
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Utilizing Synthetic Nodules for Improving Nodule Detection in Chest Radiographs.

Journal of digital imaging Mar 18, 2022
Algorithms that automatically identify nodular patterns in chest X-ray (CXR) images could benefit radiologists by reducing reading time and improving accuracy. A promising approach is to use deep learning, where a deep neural network (DNN) is trained...
Radiography, Thoracic Radiography Radiographic Image Interpretation, Computer-Assisted Humans Neural Networks, Computer Algorithms
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Spinopelvic measurements of sagittal balance with deep learning: systematic review and critical evaluation.

European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society Mar 12, 2022
PURPOSE: To summarize and critically evaluate the existing studies for spinopelvic measurements of sagittal balance that are based on deep learning (DL).
Humans Radiography Pelvis Lumbar Vertebrae Cross-Sectional Studies Deep Learning Lumbosacral Region
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