AIMC Topic: Angiography
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Unpaired Optical Coherence Tomography Angiography Image Super-Resolution via Frequency-Aware Inverse-Consistency GAN.
IEEE journal of biomedical and health informatics
Apr 4, 2025
For optical coherence tomography angiography (OCTA) images, the limited scanning rate leads to a trade-off between field-of-view (FOV) and imaging resolution. Although larger FOV images may reveal more parafoveal vascular lesions, their application i...
CMFNet: a cross-dimensional modal fusion network for accurate vessel segmentation based on OCTA data.
Medical & biological engineering & computing
Dec 13, 2024
Optical coherence tomography angiography (OCTA) is a novel non-invasive retinal vessel imaging technique that can display high-resolution 3D vessel structures. The quantitative analysis of retinal vessel morphology plays an important role in the auto...
Unsupervised adversarial neural network for enhancing vasculature in photoacoustic tomography images using optical coherence tomography angiography.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Aug 28, 2024
Photoacoustic tomography (PAT) is a powerful imaging modality for visualizing tissue physiology and exogenous contrast agents. However, PAT faces challenges in visualizing deep-seated vascular structures due to light scattering, absorption, and reduc...
Artificial Intelligence in the Angio-suite: Will Algorithms be the Copilots of the Interventional Radiologist?
Cardiovascular and interventional radiology
May 15, 2024
Classification of anatomic patterns of peripheral artery disease with automated machine learning (AutoML).
Vascular
Feb 25, 2024
AIM: The aim of this study was to investigate the potential of novel automated machine learning (AutoML) in vascular medicine by developing a discriminative artificial intelligence (AI) model for the classification of anatomical patterns of periphera...
Deep-learning-based renal artery stenosis diagnosis via multimodal fusion.
Journal of applied clinical medical physics
Feb 19, 2024
PURPOSE: Diagnosing Renal artery stenosis (RAS) presents challenges. This research aimed to develop a deep learning model for the computer-aided diagnosis of RAS, utilizing multimodal fusion technology based on ultrasound scanning images, spectral wa...
External validation of the RSNA 2020 pulmonary embolism detection challenge winning deep learning algorithm.
European journal of radiology
Feb 13, 2024
PURPOSE: To evaluate the diagnostic performance and generalizability of the winning DL algorithm of the RSNA 2020 PE detection challenge to a local population using CTPA data from two hospitals.
Improved image quality in CT pulmonary angiography using deep learning-based image reconstruction.
Scientific reports
Jan 30, 2024
We investigated the effect of deep learning-based image reconstruction (DLIR) compared to iterative reconstruction on image quality in CT pulmonary angiography (CTPA) for suspected pulmonary embolism (PE). For 220 patients with suspected PE, CTPA stu...
Improving image quality of triple-low-protocol renal artery CT angiography with deep-learning image reconstruction: a comparative study with standard-dose single-energy and dual-energy CT with adaptive statistical iterative reconstruction.
Clinical radiology
Jan 23, 2024
AIM: To investigate the improvement in image quality of triple-low-protocol (low radiation, low contrast medium dose, low injection speed) renal artery computed tomography (CT) angiography (RACTA) using deep-learning image reconstruction (DLIR), in c...
A deep learning-based algorithm improves radiology residents' diagnoses of acute pulmonary embolism on CT pulmonary angiograms.
European journal of radiology
Jan 17, 2024
PURPOSE: To compare radiology residents' diagnostic performances to detect pulmonary emboli (PEs) on CT pulmonary angiographies (CTPAs) with deep-learning (DL)-based algorithm support and without.
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