Results 61 to 70 of about 15,115 (213)

Radial capacity and hemodynamics evaluation in vitro and implantable feasibility validation in vivo of thinner bioresorbable polymer vascular stents

open access: yesBMEMat, EarlyView.
A series of in vitro experiments, numerical simulations and in vivo experiments were conducted to jointly evaluate the effects of different thicknesses of bioabsorbable polymer vascular stents on their radial capacity, hemodynamics and in vivo outcomes.
Chong Chen   +9 more
wiley   +1 more source

Drug‐coated balloons: From conventional designs to next‐generation innovations in vascular therapy

open access: yesBMEMat, EarlyView.
This review traces the evolution of drug‐coated balloons (DCBs) from conventional designs to next‐generation platforms. We highlight innovations in balloon engineering, coating technologies, and therapeutic agents that enhance localized drug delivery while addressing challenges in efficiency, safety, and biocompatibility for vascular and emerging non ...
Lu Zhang   +5 more
wiley   +1 more source

Radar High Resolution Range & Micro-Doppler Analysis of Human Motions [PDF]

open access: yes, 2009
In radar imaging it is well known that relative motion or deformation of parts of illuminated objects induce additional features in the Doppler frequency spectra.
Ghaleb, A.   +3 more
core  

Neonatal developmental and epileptic encephalopathy with movement disorder and arthrogryposis: A shared phenotype across brain‐expressed sodium channelopathies

open access: yesEpilepsia, EarlyView.
Abstract Objective Neonatal developmental and epileptic encephalopathy with movement disorder and arthrogryposis (NDEEMA) represents the most severe end of the gain‐of‐function (GOF) SCN1A disorder spectrum. Sporadic cases of congenital arthrogryposis have also been reported in individuals with SCN2A‐, SCN3A‐, and SCN8A‐related developmental and ...
Sopio Gverdtsiteli   +43 more
wiley   +1 more source

Joint sparsity-driven inversion and model error correction for radar imaging [PDF]

open access: yes, 2009
Solution of inverse problems in imaging requires the use of a mathematical model of the observation process. However such models often involve errors and uncertainties themselves. The application of interest in this paper is synthetic aperture radar (SAR)
Cetin, Mujdat   +3 more
core   +2 more sources

Deep Learning for Pretreatment Imaging‐Based Tumor and Nodal Classification in Head and Neck Squamous Cell Carcinoma: A Systematic Review and Network Meta‐Analysis

open access: yesHead &Neck, EarlyView.
ABSTRACT Background Accurate pretreatment assessment of the extent of tumor invasion and status of cervical lymph node metastasis is essential for staging and treatment planning in HNSCC. Deep learning (DL) shows promise but is limited by methodological heterogeneity. Methods We conducted a systematic review and network meta‐analysis (PRISMA). Studies (
Jannik Ketschau   +10 more
wiley   +1 more source

Non-Stationary Platform Inverse Synthetic Aperture Radar Maneuvering Target Imaging Based on Phase Retrieval

open access: yesSensors, 2018
As a powerful signal processing tool for imaging moving targets, placing radar on a non-stationary platform (such as an aerostat) is a future direction of Inverse Synthetic Aperture Radar (ISAR) systems. However, more phase errors are introduced into the
Hongyin Shi   +4 more
doaj   +1 more source

An Efficient ISAR Imaging Method for Multiple Targets [PDF]

open access: yes, 2019
This paper proposes an efficient method to obtain TSAR images of multiple targets flying in formation. The proposed method improves the coarse alignment and segmentation of the existing method.
Joo-Ho Jung   +3 more
core   +1 more source

Target Oriented High Resolution SAR Image Formation via Semantic Information Guided Regularizations

open access: yes, 2017
Sparsity-regularized synthetic aperture radar (SAR) imaging framework has shown its remarkable performance to generate a feature enhanced high resolution image, in which a sparsity-inducing regularizer is involved by exploiting the sparsity priors of ...
Hou, Biao   +3 more
core   +1 more source

Development and Release of the Munich UICC Staging Tool (MUST): Advancing UICC Staging in Real‐World Data With Insights From Pancreatic and Stomach Cancer

open access: yesInternational Journal of Cancer, EarlyView.
Accurate cancer staging is essential for cancer research and treatment evaluation. However, real‐world data often include incomplete or inconsistent UICC staging classifications. The presented Munich UICC Staging Tool (MUST) automates UICC stage derivation from TNM classifications and tumor characteristics, incorporating novel real‐world data rules to ...
Brigitte Kühnel   +18 more
wiley   +1 more source

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