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Angiography

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Improved image quality in CT pulmonary angiography using deep learning-based image reconstruction.

Scientific reports
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...

Classification of anatomic patterns of peripheral artery disease with automated machine learning (AutoML).

Vascular
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...

External validation of the RSNA 2020 pulmonary embolism detection challenge winning deep learning algorithm.

European journal of radiology
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.

Deep-learning-based renal artery stenosis diagnosis via multimodal fusion.

Journal of applied clinical medical physics
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...

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
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...

Parathyroid gland identification and angiography classification using simple machine learning methods.

BJS open
BACKGROUND: Near-infrared indocyanine green angiography allows experienced surgeons to reliably evaluate parathyroid gland vitality during thyroid and parathyroid operations in order to predict postoperative function. To facilitate equal performance ...

CMFNet: a cross-dimensional modal fusion network for accurate vessel segmentation based on OCTA data.

Medical & biological engineering & computing
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...

Unpaired Optical Coherence Tomography Angiography Image Super-Resolution via Frequency-Aware Inverse-Consistency GAN.

IEEE journal of biomedical and health informatics
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...