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Warm restart strategies are widely used in gradient-free optimization to deal with multi-model functions. In this paper, we present a novel warm restart technique by step cosine function in stochastic gradient descent method that used to train a deep convolution neural network. Three variants of step cosine function with MobileNetv2 and ResNet50 network structure are tested in our pathological lymph node PET/CT dataset. Comparing to the step function as the warm restart schedule, the proposed step cosine warm restart strategy could improve the performance of pathological lymph node image classification in terms of accuracy, sensitivity and specificity, which increased at 2.1%, 0.7% and 2.9% with MobileNetv2, and at 1.3%, 1.4% and 1.3% with ResNet50, respectively.

In this paper, we propose a framework for CT image segmentation of oil rock core. According to the characteristics of CT image of oil rock core, the existing level set segmentation algorithm is improved. Firstly, an algorithm of Chan-Vese (C-V) model is carried out to segment rock core from image background. Secondly the gray level of image background region is replaced by the average gray level of rock core, so that image background does not affect the binary segmentation. Next, median filtering processing is carried out. Finally, an algorithm of local binary fitting (LBF) model is executed to obtain the crack region. The proposed algorithm has been applied to oil rock core CT images with promising results.

The aim of this study is to present a fully automated registration algorithm that allows for alignment and errors analysis of the 3D surface model obtained from industrial computed tomography (CT) images with the computer-aided design (CAD) model. First, two pre-processing steps are executed by the algorithm namely, CAD model subdivision and representing models. Next, two improved registration procedures are applied including covariance descriptors-based coarse registration with a novel and automatic calibration, followed by a fine registration technique that utilizes an improved iterative closest points (ICP) algorithm, which is what we proposed with a novel estimation method for registration error. Finally, using a novel strategy that we proposed for error display, the quantitative data analysis results can simultaneously estimate both positive and negative deviation of the surface registration errors more precisely and fully expressed. Comparing to the original ICP algorithm, the quantitative data of experimental results demonstrate that the average registration errors of carburetors and valves are reduced by 0.80 millimeter at least. Therefore, this study demonstrates that the proposed new algorithm is not only capable of fully automating the registration of 3D surface model to a CAD model but also beneficial for quantitatively determining the surface manufacturing error more precisely.

Segmentation of CT volume data is important and useful in non-destructive testing and evaluating. To eliminate the artifacts influence, we propose a new approach of 3D defect segmentation using two steps. First of all, an initial segmentation using 3D morphological method is performed. The initial segmentation results include false defects. Secondly, resample in polar coordinates method is performed. The experimental results prove that our method is effective to correctly segment 3D defects and eliminate false segmentation. Some experiments on CT volume data with noise are made, the results show that our method is also useful.

New techniques for movable ultra-low-cost x-ray CT scanners are in instant and great needs for military, war areas, developing countries, and rural areas. In previous study, we proposed a novel CT scanning method which is based on the parallel translation of the tube/detectors. In other words, the popular slip ring is replaced by a translation based setup, and the instrumentation cost is reduced by a relaxation of the imaging speed requirement. In this paper, we furthered the exact image reconstruction algorithm for the translation based tomography scheme with two or more linear scans. The mathematical model is analyzed and the numerical simulations are conducted for different scans to validate the feasibility of the proposed scheme.

In image segmentation, Local binary fitting model (LBF) is widely used to cope with intensity inhomogeneity. It is insensitive to the initial contour with a large scale parameter and it can make the active c ontours become smooth and close to the object of the real border with the reduction of scale parameters. For the purpose of enhancing the quality of intensity inhomogeneity image segmentation, we advance a new a daptive rule to obtain the scale parameter. Experimental results on industrial CT image demonstrate that our method is insensitive to the initial contour and accurate for extracting the object.

A prototype of a Palm Pilot based pocket ECG recorder has been developed. This device consists of a custom designed ECG acquisition module and a Palm Pilot running PalmECG, a custom designed software. Standard three-lead ECG signals (Leads I, II, III) are recorded and displayed in real time on the Palm Pilot's screen. The device also records the patient's information, the start and stop time of the recording. The recorded ECG data can be replayed, and sent to a doctor by email or transmitted to a host PC or Palm device via IR beaming. After improvement, this pocket device could be used at home for remote monitoring or in the field by doctors. It may also be used as a patient activated ambulatory ECG for diagnostic evaluation of transient cardiac symptoms such as dizziness, and chest pain.

The objective of this study is to develop a phonocardiogram (PCG) acquisition and analysis instrument using virtual instrumentation technology and investigate its Internet-based application. The PCG instrument was developed using a Pentium 200 computer, a data acquisition board, and a two-channel custom designed bio-signal preamplifier. LabVIEW was used to create the instrument's front panels. Spectral and joint time-frequency analyses were implemented into the instrument. This instrument can be used to display the PCG and to analyze the individual heart sound and murmur for the detection of heart valve diseases. Using a test-bed, the PCG data acquisition and analysis were performed remotely over the Internet. Through the main PCG panel, an operator can control the acquisition and analysis of PCG signals. In the remote test, real-time transmission of the PCG signal over the Internet was possible. Remote operators were able to view smoothly scrolling PCG waveforms and could control all the acquisition parameters and perform spectral and time-frequency analyses on the acquired heart sound. This study demonstrated that a LabVIEW-based medical virtual instrument provides a low-cost and flexible solution for data acquisition and analysis of PCG. It also showed that the current Internet supports the transmission of real-time PCG signals. Compared with other telemedicine systems, this application transfers not only the medical data, but also the virtual instrument and its signal processing capability through the Internet.