AIMC Topic: Constriction, Pathologic

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Virtual indigo carmine chromoendoscopy images: a novel modality for peroral cholangioscopy using artificial intelligence technology (with video).

Gastrointestinal endoscopy
BACKGROUND AND AIMS: Accurately diagnosing biliary strictures is crucial for surgical decisions, and although peroral cholangioscopy (POCS) aids in visual diagnosis, diagnosing malignancies or determining lesion margins via this route remains challen...

Performance of Fourier-based activation function in physics-informed neural networks for patient-specific cardiovascular flows.

Computer methods and programs in biomedicine
BACKGROUND AND OBJECTIVES: Physics-informed neural networks (PINNs) can be used to inversely model complex physical systems by encoding the governing partial differential equations and training data into the neural network. However, neural networks a...

Robot-Assisted Ureteroplasty with Labial Mucosal Onlay Grafting for Long Left-Sided Proximal Ureteral Stenosis in Children and Adolescents: Technical Tips and Functional Outcomes.

Journal of endourology
To evaluate functional outcomes of robot-assisted ureteroplasty with labial mucosa grafting for long proximal ureteral stenosis (LPUS) in children and adolescents. Included in this study were 15 patients who underwent robot-assisted ureteroplasty w...

A physics-informed deep learning framework for modeling of coronary in-stent restenosis.

Biomechanics and modeling in mechanobiology
Machine learning (ML) techniques have shown great potential in cardiovascular surgery, including real-time stenosis recognition, detection of stented coronary anomalies, and prediction of in-stent restenosis (ISR). However, estimating neointima evolu...

Deep learning-based lesion detection and severity grading of small-bowel Crohn's disease ulcers on double-balloon endoscopy images.

Gastrointestinal endoscopy
BACKGROUND AND AIMS: Double-balloon endoscopy (DBE) is widely used in diagnosing small-bowel Crohn's disease (CD). However, CD misdiagnosis frequently occurs if inexperienced endoscopists cannot accurately detect the lesions. The CD evaluation may al...

A novel approach for diabetic foot diagnosis: Deep learning-based detection of lower extremity arterial stenosis.

Diabetes research and clinical practice
PURPOSE OF THE STUDY: Assessing the lower extremity arterial stenosis scores (LEASS) in patients with diabetic foot ulcer (DFU) is a challenging task that requires considerable time and efforts from physicians, and it may yield varying results. The p...

Cerebrospinal fluid flow artifact reduction with deep learning to optimize the evaluation of spinal canal stenosis on spine MRI.

Skeletal radiology
PURPOSE: The aim of study was to employ the Cycle Generative Adversarial Network (CycleGAN) deep learning model to diminish the cerebrospinal fluid (CSF) flow artifacts in cervical spine MRI. We also evaluate the agreement in quantifying spinal canal...

A multi-stage neural network approach for coronary 3D reconstruction from uncalibrated X-ray angiography images.

Scientific reports
We present a multi-stage neural network approach for 3D reconstruction of coronary artery trees from uncalibrated 2D X-ray angiography images. This method uses several binarized images from different angles to reconstruct a 3D coronary tree without a...

Coronary computed tomography angiographic detection of in-stent restenosis via deep learning reconstruction: a feasibility study.

European radiology
OBJECTIVES: Evaluation of in-stent restenosis (ISR), especially for small stents, remains challenging during computed tomography (CT) angiography. We used deep learning reconstruction to quantify stent strut thickness and lumen vessel diameter at the...