AIMC Topic: Radiographic Image Interpretation, Computer-Assisted
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Improved detection of small pulmonary embolism on unenhanced computed tomography using an artificial intelligence-based algorithm - a single centre retrospective study.
The international journal of cardiovascular imaging
Aug 28, 2024
To preliminarily verify the feasibility of a deep-learning (DL) artificial intelligence (AI) model to localize pulmonary embolism (PE) on unenhanced chest-CT by comparison with pulmonary artery (PA) CT angiography (CTA). In a monocentric study, we re...
Retrospective Studies
Female
Reproducibility of Results
Aged
Aged, 80 and over
Adult
Male
Humans
Algorithms
Pulmonary Artery
Incidental Findings
Radiographic Image Interpretation, Computer-Assisted
Feasibility Studies
Pulmonary Embolism
Computed Tomography Angiography
Middle Aged
Deep Learning
Predictive Value of Tests
Quantitative CT Imaging Features Associated with Stable PRISm using Machine Learning.
Academic radiology
Aug 26, 2024
RATIONALE AND OBJECTIVES: The structural lung features that characterize individuals with preserved ratio impaired spirometry (PRISm) that remain stable overtime are unknown. The objective of this study was to use machine learning models with compute...
Assessment of deep learning image reconstruction (DLIR) on image quality in pediatric cardiac CT datasets type of manuscript: Original research.
PloS one
Aug 26, 2024
BAKGROUND: To evaluate the quantitative and qualitative image quality using deep learning image reconstruction (DLIR) of pediatric cardiac computed tomography (CT) compared with conventional image reconstruction methods.
Renal tumor segmentation, visualization, and segmentation confidence using ensembles of neural networks in patients undergoing surgical resection.
European radiology
Aug 23, 2024
OBJECTIVES: To develop an automatic segmentation model for solid renal tumors on contrast-enhanced CTs and to visualize segmentation with associated confidence to promote clinical applicability.
Enhancing diagnosis: ensemble deep-learning model for fracture detection using X-ray images.
Clinical radiology
Aug 21, 2024
AIM: Orthopedic trauma results in the injury of bone joints and tendons of the body. A radiologist reviews and monitors large numbers of radiographs daily, which can lead to the diagnostic error. Therefore, there is a need to automate the detection o...
An efficient dual-domain deep learning network for sparse-view CT reconstruction.
Computer methods and programs in biomedicine
Aug 16, 2024
BACKGROUND AND OBJECTIVE: We develop an efficient deep-learning based dual-domain reconstruction method for sparse-view CT reconstruction with small training parameters and comparable running time. We aim to investigate the model's capability and its...
Development of a deep learning model for detecting lumbar vertebral fractures on CT images: An external validation.
European journal of radiology
Aug 15, 2024
OBJECTIVE: To develop and externally validate a binary classification model for lumbar vertebral body fractures based on CT images using deep learning methods.
Ensemble of Deep Learning Architectures with Machine Learning for Pneumonia Classification Using Chest X-rays.
Journal of imaging informatics in medicine
Aug 13, 2024
Pneumonia is a severe health concern, particularly for vulnerable groups, needing early and correct classification for optimal treatment. This study addresses the use of deep learning combined with machine learning classifiers (DLxMLCs) for pneumonia...
The Usefulness of Low-Kiloelectron Volt Virtual Monochromatic Contrast-Enhanced Computed Tomography with Deep Learning Image Reconstruction Technique in Improving the Delineation of Pancreatic Ductal Adenocarcinoma.
Journal of imaging informatics in medicine
Aug 13, 2024
To evaluate the usefulness of low-keV multiphasic computed tomography (CT) with deep learning image reconstruction (DLIR) in improving the delineation of pancreatic ductal adenocarcinoma (PDAC) compared to conventional hybrid iterative reconstruction...
Capability of multimodal large language models to interpret pediatric radiological images.
Pediatric radiology
Aug 12, 2024
BACKGROUND: There is a dearth of artificial intelligence (AI) development and research dedicated to pediatric radiology. The newest iterations of large language models (LLMs) like ChatGPT can process image and video input in addition to text. They ar...
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