AIMC Topic: Tomography, X-Ray Computed
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Online Adaptive Proton Therapy Facilitated by Artificial Intelligence-Based Autosegmentation in Pencil Beam Scanning Proton Therapy.
International journal of radiation oncology, biology, physics
Sep 20, 2024
PURPOSE: Online adaptive proton therapy (oAPT) is essential to address interfractional anatomical changes in patients receiving pencil beam scanning proton therapy. Artificial intelligence (AI)-based autosegmentation can increase the efficiency and a...
Advances in spatial resolution and radiation dose reduction using super-resolution deep learning-based reconstruction for abdominal computed tomography: A phantom study.
Academic radiology
Sep 20, 2024
RATIONALE AND OBJECTIVES: This study evaluated the performance of super-resolution deep learning-based reconstruction (SR-DLR) and compared with it that of hybrid iterative reconstruction (HIR) and normal-resolution DLR (NR-DLR) for enhancing image q...
Radiograph accelerated detection and identification of cancer in the lung (RADICAL): a mixed methods study to assess the clinical effectiveness and acceptability of Qure.ai artificial intelligence software to prioritise chest X-ray (CXR) interpretation.
BMJ open
Sep 20, 2024
INTRODUCTION: Diagnosing and treating lung cancer in early stages is essential for survival outcomes. The chest X-ray (CXR) remains the primary screening tool to identify lung cancers in the UK; however, there is a shortfall of radiologists, while de...
GC-WIR : 3D global coordinate attention wide inverted ResNet network for pulmonary nodules classification.
BMC pulmonary medicine
Sep 20, 2024
PURPOSE: Currently, deep learning methods for the classification of benign and malignant lung nodules encounter challenges encompassing intricate and unstable algorithmic models, limited data adaptability, and an abundance of model parameters.To tack...
Children Are Not Small Adults: Addressing Limited Generalizability of an Adult Deep Learning CT Organ Segmentation Model to the Pediatric Population.
Journal of imaging informatics in medicine
Sep 19, 2024
Deep learning (DL) tools developed on adult data sets may not generalize well to pediatric patients, posing potential safety risks. We evaluated the performance of TotalSegmentator, a state-of-the-art adult-trained CT organ segmentation model, on a s...
Radiomics-Based Support Vector Machine Distinguishes Molecular Events Driving the Progression of Lung Adenocarcinoma.
Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer
Sep 19, 2024
INTRODUCTION: An increasing number of early-stage lung adenocarcinomas (LUAD) are detected as lung nodules. The radiological features related to LUAD progression warrant further investigation. Exploration is required to bridge the gap between radiomi...
Comparison between artificial intelligence solution and radiologist for the detection of pelvic, hip and extremity fractures on radiographs in adult using CT as standard of reference.
Diagnostic and interventional imaging
Sep 19, 2024
PURPOSE: The purpose of this study was to compare the diagnostic performance of an artificial intelligence (AI) solution for the detection of fractures of pelvic, proximal femur or extremity fractures in adults with radiologist interpretation of radi...
Ultralow dose coronary calcium scoring CT at reduced tube voltage and current by using deep learning image reconstruction.
European journal of radiology
Sep 19, 2024
OBJECTIVE: To explore the potential of the deep learning reconstruction (DLR) for ultralow dose calcium scoring CT (CSCT) with simultaneously reduced tube voltage and current.
Artificial intelligence-assisted quantitative CT parameters in predicting the degree of risk of solitary pulmonary nodules.
Annals of medicine
Sep 19, 2024
INTRODUCTION: Artificial intelligence (AI) shows promise for evaluating solitary pulmonary nodules (SPNs) on computed tomography (CT). Accurately determining cancer invasiveness can guide treatment. We aimed to investigate quantitative CT parameters ...
Identifying severe community-acquired pneumonia using radiomics and clinical data: a machine learning approach.
Scientific reports
Sep 19, 2024
Evaluating Community-Acquired Pneumonia (CAP) is crucial for determining appropriate treatment methods. In this study, we established a machine learning model using radiomics and clinical features to rapidly and accurately identify Severe Community-A...
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