Development of a modified 3D region proposal network for lung nodule detection in computed tomography scans: a secondary analysis of lung nodule datasets.

Background: Low-dose computed tomography (LDCT) has been shown useful in early lung cancer detection. This study aimed to develop a novel deep learning model for detecting pulmonary nodules on chest LDCT images.

Methods: In this secondary analysis, three lung nodule datasets, including Lung Nodule Analysis 2016 (LUNA16), Lung Nodule Received Operation (LNOP), and Lung Nodule in Health Examination (LNHE), were used to train and test deep learning models.

Artificial intelligence evaluation of coronary computed tomography angiography for coronary stenosis classification and diagnosis.

Background: Ruling out obstructive coronary artery disease (CAD) using coronary computed tomography angiography (CCTA) is time-consuming and challenging. This study developed a deep learning (DL) model to assist in detecting obstructive CAD on CCTA to streamline workflows.

Methods: In total, 2929 DICOM files and 7945 labels were extracted from curved planar reformatted CCTA images.

Resistin as a Biomarker for the Prediction of Left Atrial Substrate and Recurrence in Patients with Drug-Refractory Atrial Fibrillation Undergoing Catheter Ablation.

Resistin is an adipocytokine that is abundantly secreted from lipid cells and is related to the inflammatory process and cardiometabolic diseases. This study aimed to examine the role of resistin on inflammation and its effect on the clinical outcome of patients with atrial fibrillation (AF) following catheter ablation.A total of 108 patients (56.

A PCB Alignment System Using RST Template Matching with CUDA on Embedded GPU Board.

The fiducial-marks-based alignment process is one of the most critical steps in printed circuit board (PCB) manufacturing. In the alignment process, a machine vision technique is used to detect the fiducial marks and then adjust the position of the vision system in such a way that it is aligned with the PCB. The present study proposed an embedded PCB alignment system, in which a rotation, scale and translation (RST) template-matching algorithm was employed to locate the marks on the PCB surface.

Expression of and long-chain non-coding RNAs in esophageal squamous cell carcinoma tissues is predictive of patient prognosis.

Introduction: The long non-coding RNAs (lncRNAs) urothelial cancer associated 1 () and metastasis associated lung adenocarcinoma transcript 1 () are known to impact cancer cell regulation. The aim of the present study was to determine the relationship between the expression of these lncRNAs in esophageal squamous cell carcinoma (ESCC) tissues and disease prognosis.

Material And Methods: The expression of and lncRNAs was assessed in ESCC and adjacent carcinoma tissues (5 cm away from the tumor) and evaluated in relation to overall survival (OS) and disease-free survival (DFS) of patients.

Evolutionary Fuzzy Block-Matching-Based Camera Raw Image Denoising.

An evolutionary fuzzy block-matching-based image denoising algorithm is proposed to remove noise from a camera raw image. Recently, a variance stabilization transform is widely used to stabilize the noise variance, so that a Gaussian denoising algorithm can be used to remove the signal-dependent noise in camera sensors. However, in the stabilized domain, the existed denoising algorithm may blur too much detail.

A modified NARMAX model-based self-tuner with fault tolerance for unknown nonlinear stochastic hybrid systems with an input-output direct feed-through term.

A modified nonlinear autoregressive moving average with exogenous inputs (NARMAX) model-based state-space self-tuner with fault tolerance is proposed in this paper for the unknown nonlinear stochastic hybrid system with a direct transmission matrix from input to output. Through the off-line observer/Kalman filter identification method, one has a good initial guess of modified NARMAX model to reduce the on-line system identification process time. Then, based on the modified NARMAX-based system identification, a corresponding adaptive digital control scheme is presented for the unknown continuous-time nonlinear system, with an input-output direct transmission term, which also has measurement and system noises and inaccessible system states.

Efficient decentralized iterative learning tracker for unknown sampled-data interconnected large-scale state-delay system with closed-loop decoupling property.

In this paper, an efficient decentralized iterative learning tracker is proposed to improve the dynamic performance of the unknown controllable and observable sampled-data interconnected large-scale state-delay system, which consists of N multi-input multi-output (MIMO) subsystems, with the closed-loop decoupling property. The off-line observer/Kalman filter identification (OKID) method is used to obtain the decentralized linear models for subsystems in the interconnected large-scale system. In order to get over the effect of modeling error on the identified linear model of each subsystem, an improved observer with the high-gain property based on the digital redesign approach is developed to replace the observer identified by OKID.

Iterative learning-based decentralized adaptive tracker for large-scale systems: a digital redesign approach.

In this paper, a digital redesign methodology of the iterative learning-based decentralized adaptive tracker is proposed to improve the dynamic performance of sampled-data linear large-scale control systems consisting of N interconnected multi-input multi-output subsystems, so that the system output will follow any trajectory which may not be presented by the analytic reference model initially. To overcome the interference of each sub-system and simplify the controller design, the proposed model reference decentralized adaptive control scheme constructs a decoupled well-designed reference model first. Then, according to the well-designed model, this paper develops a digital decentralized adaptive tracker based on the optimal analog control and prediction-based digital redesign technique for the sampled-data large-scale coupling system.

Electrophysiologic effects of 17β-estradiol on pacemaker cells in sinoatrial nodes of rabbits.

To investigate the electrophysiological effects of 17β-estradiol on pacemaker cells in sinoatrial (SA) nodes of rabbits and the underlying mechanism, intracellular microelectrode technique was used to record action potential (AP) in SA node cells of rabbits. The results showed that: (1) 17β-estradiol (1, 10, 100 μmol/L) not only significantly decreased the amplitude of action potential (APA) and the maximal rate of depolarization (V(max)), but also decreased the velocity of diastolic (phase 4) depolarization (VDD) and rate of pacemaker firing (RPF) in a concentration-dependent manner. The AP duration at 50% repolarization (APD(50)) and at 90% repolarization (APD(90)) were prolonged.

3D ROC Analysis for Medical Imaging Diagnosis.

Receiver operating characteristics (ROC) has been widely used as a performance evaluation tool to measure effectiveness of medical modalities. It is derived from a standard detection theory with false alarm and detection power interpreted as false positive (FP) and true positive (TP) respectively in terms of medical diagnosis. The ROC curve is plotted based on TP versus FP via hard decisions.

Genetic-based fuzzy image filter and its application to image processing.

In this paper, we propose a Genetic-based Fuzzy Image Filter (GFIF) to remove additive identical independent distribution (i.i.d.

Resveratrol inhibits the electrical activity of subfornical organ neurons in rat.

The effects of resveratrol on the discharges of neurons in rat subfornical organ (SFO) slices were examined by using extracellular recording technique. The results are as follows: (1) In response to the application of resveratrol (1, 5, 10 mumol/L, n=65) into the superfusate for 2 min, the spontaneous discharge rate of 60/65 (92.3%) neurons was significantly decreased in a dose-dependent manner;(2) Application of L-glutamate (0.

3D localization of clustered microcalcifications using cranio-caudal and medio-lateral oblique views.

This paper presents a 3D localization method to register clustered microcalcifications on mammograms from cranio-caudal (CC) and medio-lateral oblique (MLO) views. The method consists of three major components: registration of clustered microcalcifications in CC and MLO views, 3D localization of clustered microcalcifications and 3D visualization of clustered microcalcifications. The registration is performed based on three features, gradient, energy and local entropy codes that are independent of spatial locations of microcalcifications in two different views and are prioritized by discriminability in a binary decision tree.

Resveratrol inhibits neuronal discharges in rat hippocampal CA1 area.

The effects of resveratrol on the discharges of neurons in CA1 area of rat hippocampal slices were examined by using extracellular recording technique. The results are as follows: (1) In response to the application of resveratrol (0.05, 0.

High-frequency electrical stimulation of femoral nerve reduces infarct size following myocardial ischemia-reperfusion in rats.

The effects of femoral nerve electrostimulation (FNES) on ischemia-reperfused myocardium were examined in the urethane- anesthetized rats to determine whether FNES may provide cardioprotection and to observe the possible mechanism. The area at risk (AR) and infarct area (IA) were determined using Evans blue and nitro-blue tetrazolium staining, respectively. Infarct size (IS) was defined as 100xIA/AR (%).

Digital redesign of analog smith predictor for systems with input time delays.

This paper presents a new methodology for digitally redesigning an existing analog Smith predictor control system, such that the cascaded analog controller with input delay can be implemented with a digital controller. A traditional analog Smith predictor system is reformulated into an augmented system, which is then digitally redesigned using the predicted intersampling states. The paper extends the prediction-based digital redesign method from a delay free feedback system to an input time-delay cascaded system.