A Time-Frequency Domain Analysis Method for Variable Frequency Hopping Signal.

A variable frequency hopping (VFH) signal is a kind of frequency hopping (FH) signal that varies both in frequency and dwell time. However, in radio surveillance, the existing methods for unidentified signals using VFH cannot be effectively handled. In this paper, we proposed an improved joint analysis method based on time-frequency domain features, which adopts multi-level processing to solve the time-frequency domain feature analysis problem of the VFH signal.

Subjective and Objective Quality Assessment of Colonoscopy Videos.

Captured colonoscopy videos usually suffer from multiple real-world distortions, such as motion blur, low brightness, abnormal exposure, and object occlusion, which impede visual interpretation. However, existing works mainly investigate the impacts of synthesized distortions, which differ from real-world distortions greatly. This research aims to carry out an in-depth study for colonoscopy Video Quality Assessment (VQA).

Adaptive Cross-Feature Fusion Network With Inconsistency Guidance for Multi-Modal Brain Tumor Segmentation.

In the context of contemporary artificial intelligence, increasing deep learning (DL) based segmentation methods have been recently proposed for brain tumor segmentation (BraTS) via analysis of multi-modal MRI. However, known DL-based works usually directly fuse the information of different modalities at multiple stages without considering the gap between modalities, leaving much room for performance improvement. In this paper, we introduce a novel deep neural network, termed ACFNet, for accurately segmenting brain tumor in multi-modal MRI.

Boundary uncertainty aware network for automated polyp segmentation.

Recently, leveraging deep neural networks for automated colorectal polyp segmentation has emerged as a hot topic due to the favored advantages in evading the limitations of visual inspection, e.g., overwork and subjectivity.

Specificity-Aware Federated Learning With Dynamic Feature Fusion Network for Imbalanced Medical Image Classification.

Recently, federated learning has become a powerful technique for medical image classification due to its ability to utilize datasets from multiple clinical clients while satisfying privacy constraints. However, there are still some obstacles in federated learning. Firstly, most existing methods directly average the model parameters collected by medical clients on the server, ignoring the specificities of the local models.

Histological changes in retinal detachment: A systematic review for the clinician.

Although there have been numerous innovations in the management of retinal detachment (RD) over the past decades, there is still limited understanding of the pathophysiological processes that take place before and after repair. Summarizing key concepts using animal studies may allow for a better assessment of common pre- and postoperative microstructural abnormalities in RD. We performed a systematic literature review on Ovid MEDLINE, EMBASE, and Cochrane Controlled Register of Trials from January 1968 to January 2022, searching animal or human studies reporting retinal histologic changes following primary or induced RD.

A Meta-Analysis of Neurodevelopmental Outcomes following Intravitreal Bevacizumab for the Treatment of Retinopathy of Prematurity.

Background: Retinopathy of prematurity (ROP) is the most common cause of preventable blindness in preterm infants. First-line treatments include intravitreal bevacizumab (IVB) or laser photocoagulation (LPC).

Objectives: The aim of the study was to evaluate neurodevelopmental safety of IVB compared to LPC for ROP.

Benchmarking Polyp Segmentation Methods in Narrow-Band Imaging Colonoscopy Images.

In recent years, there has been significant progress in polyp segmentation in white-light imaging (WLI) colonoscopy images, particularly with methods based on deep learning (DL). However, little attention has been paid to the reliability of these methods in narrow-band imaging (NBI) data. NBI improves visibility of blood vessels and helps physicians observe complex polyps more easily than WLI, but NBI images often include polyps with small/flat appearances, background interference, and camouflage properties, making polyp segmentation a challenging task.

Toward Multicenter Skin Lesion Classification Using Deep Neural Network With Adaptively Weighted Balance Loss.

Recently, deep neural network-based methods have shown promising advantages in accurately recognizing skin lesions from dermoscopic images. However, most existing works focus more on improving the network framework for better feature representation but ignore the data imbalance issue, limiting their flexibility and accuracy across multiple scenarios in multi-center clinics. Generally, different clinical centers have different data distributions, which presents challenging requirements for the network's flexibility and accuracy.

Prediction of Urban Taxi Travel Demand by Using Hybrid Dynamic Graph Convolutional Network Model.

The efficient and accurate prediction of urban travel demand, which is a hot topic in intelligent transportation research, is challenging due to its complicated spatial-temporal dependencies, dynamic nature, and uneven distribution. Most existing forecasting methods merely considered the static spatial dependencies while ignoring the influence of the diversity of dynamic demand patterns and/or uneven distribution. In this paper, we propose a traffic demand forecasting framework of a hybrid dynamic graph convolutional network (HDGCN) model to deeply capture the characteristics of urban travel demand and improve prediction accuracy.

Boundary Constraint Network With Cross Layer Feature Integration for Polyp Segmentation.

Clinically, proper polyp localization in endoscopy images plays a vital role in the follow-up treatment (e.g., surgical planning).

Comparing ProKera With Amniotic Membrane Transplantation: Indications, Outcomes, and Costs.

Purpose: The aim of this study was to compare the outcomes of ProKera versus amniotic membrane transplantation (AMT) in managing ocular surface disease.

Methods: This study is a retrospective case series of patients who received either ProKera or sutured AMT for ocular surface disease. Patient demographics, treatment indications, retention time, percentage healed area, changes in visual acuity, and costs to the health care system were analyzed.

Extension of the Generalized Hydrodynamics to the Dimensional Crossover Regime.

In an effort to address integrability breaking in cold gas experiments, we extend the integrable hydrodynamics of the Lieb-Liniger model with two additional components representing the population of atoms in the first and second transverse excited states, thus enabling a description of quasi-1D condensates. Collisions between different components are accounted for through the inclusion of a Boltzmann-type collision integral in the hydrodynamic equation. Contrary to standard generalized hydrodynamics, our extended model captures thermalization of the condensate at a rate consistent with experimental observations from a quantum Newton's cradle setup.

Overview of the Canadian Clinician Investigator Trainees' research presented at the 2019 CSCI-CITAC Joint Meeting.

The 2019 Annual General Meeting and Young Investigators' Forum of the Canadian Society for Clinical Investigation / Société Canadienne de Recherche Clinique (CSCI/SCRC) and Clinician Investigator Trainee Association of Canada / Association des Cliniciens-Chercheurs en Formation du Canada (CITAC/ACCFC) was held in Banff, Alberta on November 8-10th, 2019. The theme was "Positioning Early Career Investigators for Success: Strategy and Resilience". Lectures and workshops provided knowledge and tools to facilitate the attendees' development as clinician investigators.

Genome Data Uncover Conservation Status, Historical Relatedness and Candidate Genes Under Selection in Chinese Indigenous Pigs in the Taihu Lake Region.

Chinese indigenous pig breeds in the Taihu Lake (TL) region of Eastern China are well documented by their exceptional prolificacy. There are seven breeds in this region including Meishan (MS), Erhualian (EHL), Jiaxing Black (JXB), Fengjing (FJ), Shawutou (SWT), Mi (MI), and Hongdenglong (HDL). At present, these breeds are facing a great threat of population decline, inbreeding depression and lineage admixture since Western commercial pigs have dominated in Chinese pig industry.

Novel Anti-Interleukin-1β Therapy Preserves Retinal Integrity: A Longitudinal Investigation Using OCT Imaging and Automated Retinal Segmentation in Small Rodents.

Retinopathy of prematurity (ROP) is the leading cause of blindness in neonates. Inflammation, in particular interleukin-1β (IL-1β), is increased in early stages of the disorder, and contributes to inner and outer retinal vasoobliteration in the oxygen-induced retinopathy (OIR) model of ROP. A small peptide antagonist of IL-1 receptor, composed of the amino acid sequence, rytvela, has been shown to exert beneficial anti-inflammatory effects without compromising immunovigilance-related NF-κB in reproductive tissues.

The Vision Health Research Network and its commitment to the scholarly development of its trainees.

The Vision Health Research Network (VHRN) is a provincial scientific organization that aims to improve the ocular health of patients across Quebec by supporting local research endeavors in vision health. The VHRN Student Committee, composed of 288 trainees with diverse backgrounds, has demonstrated its commitment to the scholarly development of its members by providing leadership opportunities, creating networking events, increasing visibility of researchers-in-training and encouraging professional advancement through educational workshops and funding programs. In this article, we review the contributions of the VHRN Student Committee and discuss its future projects.

The Inability of the Choroid to Revascularize in Oxygen-Induced Retinopathy Results from Increased p53/miR-Let-7b Activity.

Retinopathy of prematurity (ROP) is characterized by an initial retinal avascularization, followed by pathologic neovascularization. Recently, choroidal thinning has also been detected in children formerly diagnosed with ROP; a similar sustained choroidal thinning is observed in ROP models. But the mechanism underlying the lack of choroidal revascularization remains unclear and was investigated in an oxygen-induced retinopathy (OIR) model.

Active Event-Triggered Control for Nonlinear Networked Control Systems With Communication Constraints.

In this paper, a novel reference input and hysteresis quantizer-based active event-triggered control (RIHQAETC) scheme is proposed for nonlinear networked control systems with quantizer, networked induced delay, and packet dropout. Different from the traditional methods, such a design method is constructed involving the structure of the hysteresis quantizer. In view of the network induced delay and the potential packet dropout, our RIHQAETC method is designed to actively compensate the negative effects caused by these two issues.

Combining Local and Global Measures for DIBR-Synthesized Image Quality Evaluation.

Depth-Image-Based-Rendering (DIBR) techniques are significant for three-dimensional (3D) video applications, e.g., 3D television and free viewpoint video (FVV).

High precision calibration of optical lattice depth based on multiple pulses Kapitza-Dirac diffraction.

The precise calibration of optical lattice depth is an important step in the experiments of ultracold atoms in optical lattices. The Raman-Nath diffraction method, as the most commonly used method of calibrating optical lattice depth, has a limited range of validity and the calibration accuracy is not high enough. Based on multiple pulses Kapitza-Dirac diffraction, we propose and demonstrate a new calibration method by measuring the fully transfer fidelity of the first diffraction order.