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检索条件"任意字段=International Congress on Image and Signal Processing, BioMedical Engineering and Informatics"

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Thickness measurements of ten intra-retinal layers from optical coherent tomography images using a super-pixels and manifold ranking approach

Thickness measurements of ten intra-retinal layers from opti...

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international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Zhijun Gao Wei Bu Xiangqian Wu Yalin Zheng College of Computer and Information Engineering Heilongjiang University of Science and Technology Harbin China School of Computer Science and Technology Harbin Institute of Technology Harbin China Dept of Media Technology & Art Harbin Institute of Technology Harbin China Department of Eye and Vision Science University of Liverpool UK

ISBN: (纸本)9781509037117

The purposes of this paper are to calculate exactly the mean thickness, plot the thickness maps, and depict the early treatment diabetic retinopathy study (ETDRS) charts for ten intra-retinal layers by spectral domain optical coherence tomography(OCT). Using our previously the reported segmented method with a simple linear iterative clustering (SLIC) super-pixels and manifold ranking (SLIC_MR), the ten intra-retinal layers were fast and exactly segmented in 3-D OCT dataset, includes 55 B-scan images from 11 different healthy adult subjects. By our definitions of the sensitivity and specificity, we compared the segmented results with the recent graph-based method for the main layers in dataset. The experimental results demonstrated that the SLIC_MR method outperformed the graph-based method. The thickness maps were plotted in the ten intra-retinal layers and the overall layer, the ETDRS charts were depicted in the 9 sectors of each intra-retinal layer and the overall layer, and the bar graph displayed the mean and standard deviation of macular thickness in 9 sectors for ten retinal layers and the overall layer. The mean thickness of the central foveal area displayed the minimum thickness in layers 1, 2, 3, 4, 5 and the overall, and the maximum thickness in the central foveal area of the 6th layer. Both layers 4 and 5 have the similar mean thickness in each sector.

关键词： Retina image segmentation Manifolds Standards Sensitivity Observers Thickness measurement

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Monte Carlo dose estimation in patient-specific volume mesh from CT images

Monte Carlo dose estimation in patient-specific volume mesh ...

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international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： S. Morató R. Miró B. Juste G. Verdú A. Santos Universitat Politècnica de València ISIRYM Institute for Industrial Radiophysical and Environmental Safety Spain Consorci Hospitalari Provincial de Castelló Castelló de la Plana Spain

ISBN: (纸本)9781509037117

Radiation treatments are in continuous evolution and the use of increasingly advanced technologies enables personalized treatments. According to this, the work presented is focused on the 3D computed reconstruction of segmented CT images taken from an anthropomorphic phantom (RANDO phantom) using unstructured meshes. This phantom model is used to simulate dose distribution during a beam irradiation with Monte Carlo code. Searching for the most appropriate and rapid methodology for meshing the segmented phantom is the main goal of the present work. The use of different coupled softwares, as image segmentation software or meshing geometry software were necessary. Besides, several FORTRAN routines were coded for conversion formatting to Monte Carlo code and dose calculation. This study has used the last version of MCNP (v.6.1.1) Monte Carlo code to simulate a RANDO phantom irradiation. This new code version presents a new tool to improve geometry description by the importation of meshed models. The generated meshed head model is included in a Monte Carlo model of photon beam transport emitted by a medical LINear ACcelerator (LinAc). Results have been compared with values obtained by experimental measurements in different positions inside the phantom using High-Sensitivity MOSFET (Metal Oxide Semiconductor Field Effect Transistor) dosimeters. Monte Carlo results are in good agreement with experimental values, which demonstrate the validity and accuracy of the Monte Carlo method to estimate dose. The innovation of using meshed geometries in these calculations, shows an important advantage defining complex geometries as human anatomy.

关键词： Phantoms Monte Carlo methods MOSFET Geometry image segmentation Head Linear particle accelerator

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Remote and collaborative medical image visualization computing platform

Remote and collaborative medical image visualization computi...

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international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Zhuofu Deng Zhiliang Zhu Yen-Wei Chen College of Software Engineering Northeastern University Shenyang P. R. China College of Information Science & Engineering Ritsumeikan University Kusatsu Shiga Japan

ISBN: (纸本)9781509037117

With the development of computing capability and display size in computing hardware, mobile terminals like iPhone or iPad have been more and more accepted as a tool to help radiologists to examine medical images of patients in order to give more accurate diagnostic conclusion through server. The radiologists can observe the images by interacting them with different hand gestures to translate, rotate and zoom in or out the objects in the medical images of the mobile terminals. However, because of the requirements of remote medical, we need a system that should have one kind of function-collaboration, which means that when different radiologists located at different places hold a remote teleconference to discuss the same medical images for difficult miscellaneous disease, one expert wishes that when he changes the position of object in the images the other experts will see the changes at once so that they can keep accordance all the time to talk over the focus with voice communication and other auxiliary tools. This paper developed a remote and collaborative medical image visualization system where medical experts can work collaboratively with each other. In the proposed application, the server system can file the data of patients like CT, MR images and other information. Meanwhile, the terminal clients can download the medical 2D data and rendering them on itself including 3D image reconstruction, moreover the server can also support teleconference mode that the experts in different places discuss one patient's illness with this system like in the same location of conference. Finally, the performance issues regarding the remote 3D visualization of the medical images platform over the wireless network of the proposed system were also discussed. The result demonstrated that the proposed remote and collaborative medical image visualization computing platform could provide a perfect interactive experience in the WLAN and 4G network.

关键词： Rendering (computer graphics) Medical diagnostic imaging Three-dimensional displays Servers Data visualization Mobile communication

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Parallel Subgraph Matching on Massive Graphs

Parallel Subgraph Matching on Massive Graphs

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international congress on image and signal processing, biomedical engineering and informatics

作者： Bo Suo Zhanhuai Li Wei Pan School of Computer Science and Engineering Northwestern Polytechnical University

ISBN: (纸本)9781509037117

While numerous applications, such as social networks, protein-protein interaction networks, and bibliographic networks, mainly consist of graph-structured data, massive graphs, of which the scales range from million nodes to billion nodes, are common-place. Searching within these kinds of graphs is urged to be efficient. Unfortunately, since the subgraph isomorphism problem is NP-complete, querying on large graphs is still challenging. Most of existing approaches employ various pruning rules to facilitate the matching process on a single machine. When a data graph is large and dense, auxiliary information, known as index, and intermediate results could easily run out of computational resources. Recently, inspired by the popularity of parallel programming models, such as MapReduce and Pregel, there is a trend to solve the subgraph matching problem upon them. However, caused by the incompleteness of graph data in each cluster machine, parallel solutions of subgraph matching are often proposed in a brute-force way. In this paper, we propose a parallel subgraph matching framework which uses k-hop replication based partitioning approach to distribute the graph data across cluster machines. Benefiting from the proposed framework, the completeness of local searching can be ensured. Hence, previous studies on indexing graph data become usable and valuable for the parallel graph querying problem. For the consideration of efficiency, taking a light-weight neighborhood-based index as an example, we also propose two potential optimization opportunities for reducing intermediate results. We implement the proposed framework on Hadoop/MapReduce. Our experimental results on real-world data sets demonstrate its effectiveness on very large graphs.

关键词： graph data Parallel Lines machine Parallel programming

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Post-Stroke Asymmetry of Muscle Contractions for Knee Flexion and Extension During Walking

Post-Stroke Asymmetry of Muscle Contractions for Knee Flexio...

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international congress on image and signal processing, biomedical engineering and informatics

作者： Wei Wang Ke Li Na Wei Cuiping Yin Shouwei Yue Institute of Biomedical Engineering School of Control Science and Engineering Shandong University Department of Geriatrics Qilu Hospital Shandong University Department of Physical Medicine and Rehabilitation Qilu Hospital Shandong University

ISBN: (纸本)9781509037117

Patients with stroke usually have abnormal gait during walking. A hallmark of the post-stroke gait is the decreased knee flexion on the paretic leg compared to the non-paretic side. The objective of this study was to investigate the muscle contractions that are potentially responsible for the asymmetry of knee flexion in post-stroke patient. Ten stroke patients and 10 age- and sex-matched healthy controls were recruited. Kinematic signals were recorded using a motion analysis system by capturing the reflective markers attached on the both legs. Surface electromyography (sEMG) signals were collected using on the rectus femoris (RF) muscle, the biceps femoris (BF) muscle and the gastrocnemius (GAS) muscle. Asymmetry ratio of the knee angle range (KAR), as well as the root mean square error (RMSE) of the sEMG during knee joint flexion and extension within one gait cycle was calculated. We found that most patients were different from healthy subjects in the asymmetry ratio of KAR during flexion (p < 0.05), and extension (p < 0.01). The RMSE of the RF of non-paretic side in stroke patient was different from that of healthy control during extension (p < 0.05). There were differences in RMSEs of the GAS of both sides between two groups during flexion in paretic side (p < 0.05) and non-paretic side (p < 0.05). Differences were found in RMSEs of GAS of both stroke (p < 0.05) and control (p < 0.05) between two sides during flexion. Comparing the gait symmetry and the situations of muscle contractions between people after stroke and healthy people could guide the clinical rehabilitation of stroke patients.

关键词： muscle contraction gait symmetry stroke electromyography

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Joint analysis of multi-level functional brain networks

Joint analysis of multi-level functional brain networks

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international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Huiwen Luo Weibei Dou Yu Pan Yueheng Wang Yujia Mu Yudu Li Xiaojie Zhang Quan Xu Shuyu Yan Yuanyuan Tu Department of Electronic Engineering Tsinghua University Beijing China Department of Rehabilitation Tsinghua Changgung Hospital Beijing China

ISBN: (纸本)9781509037117

Building brain networks based on functional Magnetic Resonance Imaging (fMRI) signal is one of the efficient methods to study functional connectivity of human brain. Various methods of constructing brain network will lead to different results. It is wondered which method is reliable. Therefore, it is necessary to set up a synthetical framework of brain network analysis to study the functional connectivity. A joint analysis method of multi-level functional brain networks is proposed in this paper. These networks are constructed based on different correlation matrixes of fMRI signal between voxels and between anatomical areas (regions) of brain. They are called whole brain network of voxel-based and region-based, and local network of voxel-based inside brain regions. The joint analysis implements feature combination of global and local network attributes to measure or evaluate the brain region characteristics towards reducing uncertainty. The resting-state fMRI data of 37 subjects (22 normal subjects and 15 patients with spinal cord injury (SCI)) have been used to test the proposed method. Three-level functional connectivity networks are jointly analyzed to combine the two-type significant features, the significant differences between normal and patient, and the significant correlations between network features and clinic function scores of patient. The results of the features combination are validated by the specific Brodmann area (BA) regions characterized by the similar and the complementary features, and most of them belong to the dorsolateral prefrontal cortex (DLPFC) and correspond with SCI disease. Compared with network analysis of the commonly used voxel-based whole brain network, the proposed joint analysis method can provide more central, more robust and more reliable evidences. Overall, the proposed method takes advantages of different functional networks and shows the complete discovery to us by the consistency and mutual complementation of these kinds of

关键词： Correlation Feature extraction Brain Correlation coefficient Magnetic resonance imaging Reliability Data mining

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An Adaptive Reconfigurable Radix-2~n FFT/IFFT Architecture

An Adaptive Reconfigurable Radix-2~n FFT/IFFT Architecture

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international Conference on informatics, Electronics and Vision

作者： Md. Jahiruzzaman Masud An Nur Islam Fahim Sakib Mostafa A. B. M. Aowlad Hossain Dept. of Electronics and Communication Engineering Khulna University of Engineering & Technology Khulna-9203 Bangladesh

ISBN: (纸本)9781509012701

The suitability of the Discrete Fourier Transform (DFT) from arbitrary viewpoints is an important requirement for different tasks which covers various area of engineering including signal processing, image processing, quantum computing, digital communication system, biomedical sector and so on. For the execution of DFT, several computation schedule based on different structural patterns have been proposed and among these the widely used practical design is Radix-2~n N points Fast Fourier Transform (FFT/IFFT) which has the order of complexity of some crucial tasks is N-log_2 N, where N and n are the FFT points and stages respectively. The problems of Radix-2~n N points FFT/IFFT is that they are architectural based, non-reconfigurable and the input-output data are generally not in sequence. In this paper, we proposed two algorithmic schematic structures to compute the DFT & IDFT which are adaptive, reconfigurable and compatible to any 2~n point FFT/IFFT where the input-output data are in sequences. The proposed architecture uses an adaptive feedback single butterfly stage that will reduce the hardware cost. This architecture is implemented on MATLAB and the computation time for different N points FFT/IFFT are investigated.

关键词： DFT FFT/IFFT Reconfigurable architecture

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image super-resolution via sparse coding for Chinese license plate recognition 8

Image super-resolution via sparse coding for Chinese license...

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8th international congress on image and signal processing, CISP 2015

作者： Hao, Ni Liu, Fanghua Ruan, Ruolin School of Electronic and Information Engineering Hubei University of Science and Technology Xianning China School of Biomedical Engineering Hubei University of Science and Technology Xianning China

ISBN: (纸本)9781467390989

Some plate recognition systems can not recognize the low-resolution license plate images correctly because the resolution of the input plate image is very low. The proposed method in this paper enhances the resolution of the Chinese license plate image via sparse coding. It employs dictionary learning to get the optimal overcomplete dictionary pairs and introduces the regularization terms to recover the high-resolution plate image. Experiments show that the plate image recovered by the proposed method can be well recognized. That is, the proposed single image super-resolution method in this paper can promote the plate recognition effectively. © 2015 IEEE.

关键词： image enhancement

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Single image super-resolution via online dictionary learning with double regularization parameters 8

Single image super-resolution via online dictionary learning...

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8th international congress on image and signal processing, CISP 2015

作者： Hao, Ni Wang, Jianfeng Ruan, Ruolin School of Electronic and Information Engineering Hubei University of Science and Technology Xianning China Center of Network Management Hubei University of Science and Technology Xianning China School of Biomedical Engineering Hubei University of Science and Technology Xianning China

ISBN: (纸本)9781467390989

The performance of single image super-resolution (SR) based on sparse coding is promising but the artifacts are obvious. In order to promote the SR efficiency, the proposed algorithm employs Online Dictionary Learning (ODL) to train the overcomplete dictionaries separately to reduce the artifacts. It sets two different regularization parameters in the phases of dictionary learning and image reconstruction. They are tuned independently to get the best results. In the experiments, the PSNRs are 0.41dB higher than Sparse Coding Super-Resolution (SCSR) and 0.28dB higher than ODL SR algorithm in average. The proposed method can eliminate the artifacts and recover the texture details efficiently. © 2015 IEEE.

关键词： image reconstruction

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Adaptive low-dose CT reconstruction

Adaptive low-dose CT reconstruction

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congress on image and signal processing, CISP

作者： Bingjie Zhao Cuixia Feng Congcong Feng Junhai Wen Department of Biomedical Engineering Beijing Institute of Technology Beijing China

With computed tomography (CT) technology more and more widely used in clinical applications, low-dose CT arouses people's attention gradually. In this paper, we propose an adaptive low-dose CT reconstruction framework. This framework is based on the iterative algorithm, and tries to find the fewest projection angles adaptively insuring the image quality, achieves the goal of reducing the radiation dose at last. The simulation results show that this adaptive low-dose CT reconstruction framework can find the fewest projection angles adaptively according to the requirement of image quality.

关键词： image reconstruction Computed tomography Entropy image quality X-rays Standards TV

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