AIMC Topic: Angiography

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DDU-Net: learning complex vascular topologies with KAN-Swin transformers and double dynamic upsampler.

Biomedical physics & engineering express
To segment complex vascular topologies in Optical Coherence Tomography Angiography (OCTA), we introduce DDU-Net. This work addresses the theoretical limitations of standard Swin Transformers, whose internal Multi-Layer Perceptron (MLP) blocks use fix...

Improve deep learning-based reconstruction of optical coherence tomography angiography by siamese U-Net.

Biomedical physics & engineering express
Optical coherence tomography angiography (OCTA), as a functional imaging based on OCT, has found successful medical applications. OCTA produces vasculature imaging using blood flow motion as an intrinsic contrast agent. To date, the prevailing OCTA a...

Comparative analysis of robotic assisted vs. traditional spinal angiography in a large single-center experience.

Journal of the neurological sciences
BACKGROUND: Spinal angiography (SA) remains the gold standard for evaluating spinal cord vasculature, but traditional approaches expose operators and patients to significant ionizing radiation. Robotic-assisted platforms offer potential advantages th...

DERMA-OCTA: A Comprehensive Dataset and Preprocessing Pipeline for Dermatological OCTA Vessel Segmentation.

Scientific data
Optical coherence tomography angiography (OCTA) has emerged as a promising tool for non-invasive vascular imaging in dermatology. However, the field lacks standardized methods for processing and analyzing these complex images, as well as sufficient a...

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...

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...

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...

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...

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...