AIMC Topic: Radiography
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Deep learning based de-overlapping correction of projections from a flat-panel micro array X-ray source: Simulation study.
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)
May 19, 2023
PURPOSE: Flat-panel X-ray source is an experimental X-ray emitter with target application of static computer tomography (CT), which can save imaging space and time. However, the X-ray cone beams emitted by the densely arranged micro-ray sources are o...
Estimating Uncertainty in Neural Networks for Cardiac MRI Segmentation: A Benchmark Study.
IEEE transactions on bio-medical engineering
May 19, 2023
OBJECTIVE: Convolutional neural networks (CNNs) have demonstrated promise in automated cardiac magnetic resonance image segmentation. However, when using CNNs in a large real-world dataset, it is important to quantify segmentation uncertainty and ide...
A survey on automatic generation of medical imaging reports based on deep learning.
Biomedical engineering online
May 18, 2023
Recent advances in deep learning have shown great potential for the automatic generation of medical imaging reports. Deep learning techniques, inspired by image captioning, have made significant progress in the field of diagnostic report generation. ...
Performance of ChatGPT on a Radiology Board-style Examination: Insights into Current Strengths and Limitations.
Radiology
May 16, 2023
Background ChatGPT is a powerful artificial intelligence large language model with great potential as a tool in medical practice and education, but its performance in radiology remains unclear. Purpose To assess the performance of ChatGPT on radiolog...
Artificial intelligence in radiology - beyond the black box.
RoFo : Fortschritte auf dem Gebiete der Rontgenstrahlen und der Nuklearmedizin
May 9, 2023
BACKGROUND: Artificial intelligence is playing an increasingly important role in radiology. However, more and more often it is no longer possible to reconstruct decisions, especially in the case of new and powerful methods from the field of deep lear...
Explainable AI in radiology: a white paper of the Italian Society of Medical and Interventional Radiology.
La Radiologia medica
May 8, 2023
The term Explainable Artificial Intelligence (xAI) groups together the scientific body of knowledge developed while searching for methods to explain the inner logic behind the AI algorithm and the model inference based on knowledge-based interpretabi...
Sociodemographic Variables Reporting in Human Radiology Artificial Intelligence Research.
Journal of the American College of Radiology : JACR
May 5, 2023
PURPOSE: Artificial intelligence (AI) is rapidly reshaping how radiology is practiced. Its susceptibility to biases, however, is a primary concern as more AI algorithms become available for widespread use. So far, there has been limited evaluation of...
Deep-Learning-Based Detection of Vertebral Fracture and Osteoporosis Using Lateral Spine X-Ray Radiography.
Journal of bone and mineral research : the official journal of the American Society for Bone and Mineral Research
May 4, 2023
Osteoporosis and vertebral fractures (VFs) remain underdiagnosed. The addition of deep learning methods to lateral spine radiography (a simple, widely available, low-cost test) can potentially solve this problem. In this study, we develop deep learni...
Automatic Spine Segmentation and Parameter Measurement for Radiological Analysis of Whole-Spine Lateral Radiographs Using Deep Learning and Computer Vision.
Journal of digital imaging
May 2, 2023
Radiographic examination is essential for diagnosing spinal disorders, and the measurement of spino-pelvic parameters provides important information for the diagnosis and treatment planning of spinal sagittal deformities. While manual measurement met...
Collimation border with U-Net segmentation on chest radiographs compared to radiologists.
Radiography (London, England : 1995)
May 2, 2023
INTRODUCTION: Chest Radiography (CXR) is a common radiographic procedure. Radiation exposure to patients should be kept as low as reasonably achievable (ALARA), and monitored continuously as part of quality assurance (QA) programs. One of the most ef...
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