PCI

Multi-Scale Reconstruction of Undersampled Spectral-Spatial OCT Data for Coronary Imaging Using Deep Learning.

Coronary artery disease (CAD) is a cardiovascular condition with high morbidity and mortality. Intravascular optical coherence tomography (IVOCT) has been considered as an optimal imagining system for the diagnosis and treatment of CAD. Constrained by Nyquist theorem, dense sampling in IVOCT attains high resolving power to delineate cellular structures/features. There is a trade-off between high s...

Active tactile sensing of small insect force by a soft microfinger toward microfinger-insect interactions.

Human-robot interaction technology has contributed to improving sociality for humanoid robots. At scales far from human scales, a microrobot can interact with an environment in a small world. Microsensors have been applied to measurement of forces by flying or walking insects. Meanwhile, most previous works focused on the measurement of the behavior of insects. Here, we propose microrobot-insect i...

Improvement in Image Quality and Visibility of Coronary Arteries, Stents, and Valve Structures on CT Angiography by Deep Learning Reconstruction.

OBJECTIVE: This study aimed to investigate whether a deep learning reconstruction (DLR) method improves the image quality, stent evaluation, and visib...

Wireless Miniature Magnetic Phase-Change Soft Actuators.

Wireless miniature soft actuators are promising for various potential high-impact applications in medical, robotic grippers, and artificial muscles. H...

Evaluation of a hybrid pipeline for automated segmentation of solid lesions based on mathematical algorithms and deep learning.

We evaluate the accuracy of an original hybrid segmentation pipeline, combining variational and deep learning methods, in the segmentation of CT scans...

Coronary Artery Stent Evaluation by CTA: Impact of Deep Learning Reconstruction and Subtraction Technique.

Coronary CTA with hybrid iterative reconstruction (HIR) is prone to false-positive results for in-stent restenosis due to stent-related blooming arti...

Development and validation of a predictive model for peripherally inserted central catheter-related thrombosis in breast cancer patients based on artificial neural network: A prospective cohort study.

BACKGROUND: Peripherally inserted central catheters have been extensively applied in clinical practices. However, they are associated with an increase...

Adaptive wireless millirobotic locomotion into distal vasculature.

Microcatheters have enabled diverse minimally invasive endovascular operations and notable health benefits compared with open surgeries. However, with...

Use of Machine Learning to Develop Prediction Models for Mortality and Stroke in Patients Undergoing Balloon Aortic Valvuloplasty.

OBJECTIVE: To develop an artificial intelligence, machine learning prediction model for estimating in-hospital mortality and stroke in patients underg...

Deep Learning-Based Intraoperative Stent Graft Segmentation on Completion Digital Subtraction Angiography During Endovascular Aneurysm Repair.

PURPOSE: Modern endovascular hybrid operating rooms generate large amounts of medical images during a procedure, which are currently mostly assessed b...

Robot-Assisted Laparoscopic Calyceo-Pyelostomy for Vascular Compression of the Upper Calyx (Fraley Syndrome).

Fraley's Syndrome is a rare anatomic vascular malformation described in 1966 where an aberrant crossing vessel compresses the upper infundibulum and l...

Ultrasonic Image Feature Analysis under Deep Learning Algorithm to Evaluate the Efficacy of Drug-Coated Balloon for Treatment of Arteriosclerotic Occlusion.

In order to explore the adoption of ultrasonic images under deep learning (DL) algorithm to evaluate the efficacy of drug-coated balloon (DCB) for tre...

Machine learning model prediction of 6-month functional outcome in elderly patients with intracerebral hemorrhage.

Spontaneous intracerebral hemorrhage (ICH) has an increasing incidence and a worse outcome in elderly patients. The ability to predict the functional ...

Exploiting exercise electrocardiography to improve early diagnosis of atrial fibrillation with deep learning neural networks.

Atrial fibrillation (AF) is the most common type of sustained arrhythmia. It results from abnormal irregularities in the electrical performance of the...

V08-07 Robotic Pyeloplasty of Lower Pole Moiety in a 2 Month Old Infant With Cutaneous Pyeloureteral (CPU) Stent. Erratum.

Fully automated platelet differential interference contrast image analysis via deep learning.

Platelets mediate arterial thrombosis, a leading cause of myocardial infarction and stroke. During injury, platelets adhere and spread over exposed su...

Ultrasound Image under Artificial Intelligence Algorithm to Evaluate the Intervention Effect of Accelerated Rehabilitation Surgery Nursing on Laparoscopic Hysterectomy.

To explore the application value of accelerated rehabilitation surgery (ERAS) nursing in laparoscopic total hysterectomy, 120 patients who underwent l...

Deep Learning-Based Emergency Care Process Reengineering of Interventional Data for Patients with Emergency Time-Series Events of Myocardial Infarction.

This paper proposes a representation learning framework HE-LSTM model for heterogeneous temporal events, which can automatically adapt to the multisca...

Usefulness of Thromboelastography for Perioperative Evaluation of Hemostatic Profile in Patients with Primary Brain Tumors Undergoing Surgery.

CONTEXT: Hemostatic abnormalities are more common in patients with brain tumors than systemic malignant diseases. Conventional coagulation tests (CCT)...

Instance segmentation convolutional neural network based on multi-scale attention mechanism.

Instance segmentation is more challenging and difficult than object detection and semantic segmentation. It paves the way for the realization of a com...