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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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3D Convolutional Networks Based Automatic Diagnosis of Alzheimer's Disease Using Structural MRI 12

3D Convolutional Networks Based Automatic Diagnosis of Alzhe...

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12th international congress on image and signal processing, biomedical engineering and informatics, CISP-BMEI 2019

作者： Yu, Xinying Peng, Bo Shi, Jun Zhu, Jianbin Dai, Yakang Shanghai Institute for Advanced Communication and Data Science School of Communication and Information Engineering Shanghai University China Suzhou Institute of Biomedical Engineering and Technology Chinese Academy of Sciences Suzhou China Suzhou Key Laboratory of Medical Health Information Technology Suzhou China Nanjing Guoke Medical Engineering Technology Development co. LTD Nanjing China Jinan Guoke Medical Engineering Technology Development co. LTD Jinan China Suzhou Hospital Affiliated Nanjing Medical University Suzhou215153 China Suzhou Science and Technology Town Hospital Suzhou Jiangsu Province215153 China

ISBN: (纸本)9781728148526

Early diagnosis of Alzheimer's disease (AD) can help take timely treatment before patients suffer from irreversible brain damage. However, current studies using manually feature extraction and 2D CNN methods cannot make the classification performance optimized. We proposed an approach using 3D convolutional neural network (CNN) to diagnose AD and mild cognitive impairment (MCI), which is the prodromal stage of AD, from structural magnetic resonance images. Subjects of 150 AD, 129 MCI, and 112 normal controls (NC) from the Alzheimer's Disease Neuroimaging Initiative dataset were used in this study. Specifically, weights of a 3-class network were trained to initialize the 2-class network and fine-tuned, which saves time and avoids overfitting. The experimental results show that our 3D-sVoxCNN model significantly improves the classification performance with the accuracy of 95.05% (AD vs MCI vs NC), 99.47% (AD vs. NC), 98.32% (MCI vs. NC), and 98.32% (AD vs. MCI). © 2019 IEEE.

关键词： Magnetic resonance imaging

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Diagnosis of Thyroid Nodules in Ultrasound images Using Two Combined Classification Modules

Diagnosis of Thyroid Nodules in Ultrasound Images Using Two ...

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

作者： Heng Zhang Chongke Zhao Lehang Guo Xiaolong Li Ye Luo Janwei Lu Huixiong Xu School of Software Engineering Tongji University Shanghai China Shanghai Tenth People's Hospital Shanghai China Institute of Translational Medicine Tongji University Shanghai China School of Medicine Tongji University Shanghai China

Ultrasonography is a common modality for diagnosing thyroid nodules. Computer-aided classification of benign and malignant thyroid nodules in the ultrasound images is meaningful. A key challenge in this issue is that a lot of ultrasound images without obvious benign or malignant features are hindering deep learning model to extract effective features. Here, a novel method using two combined classification modules is proposed to separate and classify those images. Firstly, we adopt multi-fold cross-validation based a CNN model to pick out ultrasound images that hard to recognize. Then we add new labels to those images and put them back to the dataset that will be trained with the CNN model to form a tripartite classification module. Finally, a binary classification module will be trained exclusively to discriminate those obscure images. Experimental results on 4148 ultrasound images show that the proposed method lead to excellent performance, with an accuracy of 0.804, which demonstrate the value of this method.

关键词： Ultrasonic imaging Thyroid Cancer Training image recognition Data models Feature extraction

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Theta Synchronization and ERPs in Deception Detection

Theta Synchronization and ERPs in Deception Detection

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

作者： Min Zhao Nini Rao Chunlin Zhao Information Engineering Academy People's Armed Police of Engineering University Xi'an china University of Electronic Science and Technology of China Chengdu china

Although event related potentials (ERPs) have been used for the deception detection, deception-related changes in the electroencephalogram (EEG) remain to be established. The purpose of this research is to test the effect of theta oscillation in information concealing. EEG is recorded when healthy volunteers performed a deceptive task in a card-like version of the Concealed Information Test (CIT) paradigm. Data were analyzed by using event-related synchronization. A significant effect in theta power was recorded. The probe stimulus elicited larger theta synchronization than the irrelevant stimulus in the 200-500 ms post-stimulus data for deceptive participants. This effect was not observed in the control group. The theta synchronization effect overlapped with the classical ERP P300 effect but with marked difference in electrodes. The theta synchronization effect was strongest on the Fz electrode. The P300 effect was strongest on the Pz electrode. Our results indicated that theta synchronization is correlated with concealing information and might reflect some changes in related deception.

关键词： Electrodes Probes Erbium Synchronization Electroencephalography Task analysis Heart

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Research on digitally reconstructed radiograph algorithm improvement based on computed tomography image 11

Research on digitally reconstructed radiograph algorithm imp...

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11th international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Li, Tongying Zhu, Hongbo Nantong Polytech Coll Nantong 226002 Jiangsu Peoples R China Nanjing Univ Posts & Telecommun Key Lab Wideband Wireless Commun Nanjing 210003 Jiangsu Peoples R China

ISBN: (纸本)9781538676042

A fast ray tracing algorithm from sequence tomographic images for digitally reconstructed radiograph was presented. A ray tracing algorithm based on vector was adopted, and using computed tomography data simulated the absorption of radiation from human tissues,. The algorithm only has the addition and the subtraction operation, and the computation is simple. The algorithm does not need to obtain the corresponding intersection by solving the equation, and it has the characteristics of short imaging time and fast computing speed. At the same time, this paper improves the algorithm of 3D prosthesis storage and retrieval, and the algorithm realized online digitally reconstructed radiograph calculation, which greatly improves the computing speed. Finally, the digitally reconstructed radiograph images obtained in this paper were further processed digitally to improve their practical value.

关键词： digitally reconstructed radiograph computed tomography simulation ray tracing virtual simulation virtual radiograph

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Research on an image High Intensive Encryption Way Based on the Chaos Theory and DNA Coding

Research on an Image High Intensive Encryption Way Based on ...

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

作者： Kaishi Li Zhen Su School of Information and Communication Engineering Communication University of China Beijing China

With the development of Internet information technology, reliable transmission of multimedia data such as images and videos is becoming more and more important. For the traditional data encryption technology can not be effectively used in the current image encryption, this paper proposes a color image encryption algorithm based on two hyperchaotic systems and DNA coding and studies its performance. Firstly, a color image is divided into three channels: R, G, and B. Then, the random matrix generated by Logistic mapping and the three-channel matrix of plaintext image are partitioned into blocks. The random sequence generated by Chen hyperchaotic system is used to determine the DNA encoding and decoding mode and DNA operation mode of each channel of plaintext image RGB and each sub-block of random matrix. The DNA encoding and decoding mode and the DNA operation mode of each sub-block are performed in parallel and the Logistic chaotic system is used to map out the sequence to perform row and column replacement on the ciphertext image. Finally merge the encrypted sub-blocks to get the encrypted image. At the same time, the paper analyzes the encryption effect by histograms of R, G and B channels, information entropy, adjacent pixel correlation and key sensitivity simulation. By comparing the simulation results with other algorithms, it can be concluded that the image encryption effect is objective and has the characteristics of high security, large key space and strong anti-attack performance.

关键词： DNA Encryption image coding Chaotic communication Decoding Channel coding

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Robust Dual images Super-resolution 11

Robust Dual Images Super-resolution

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11th international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Zhang, Xiaohong Zhang, Yun Qian, Guiping Qin, Aihong Commun Univ Zhejiang Sch New Media Hangzhou Zhejiang Peoples R China Commun Univ Zhejiang Inst Radio & TV Technol Hangzhou Zhejiang Peoples R China

ISBN: (纸本)9781538676042

With the developing of 3D mobile phone, there are more and more dual images which seen from slightly different angles caught by two mobile phone cameras. The images caught by mobile phone camera usually have lower resolution (LR) than the images caught by normal camera. To solve this problem, this paper proposes a robust Bayesian SR method to recover high-frequency information from dual LR images, which solves the registration, interpolation, kernel estimation, restoration, and post-processing problems simultaneously. It's noticed that the blur kernel (Gaussian blur kernel) of the proposed SR processing is recalculated in iterations, other than a constant kernel as usual. Our experimental results show great visual improvement and a suppressing of high-frequency artifacts.

关键词： Kernel Mobile handsets image reconstruction Bayes methods Spatial resolution Cost function

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Evaluation of Retinal SFS Reconstruction with OCT images 11

Evaluation of Retinal SFS Reconstruction with OCT Images

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11th international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Wang, Peipei Dai, Fengliang Zhao, Mengdie Liu, Xiaojin Sun, Jiuai Univ Shanghai Sci & Technol Sch Med Instrument & Food Engn Shanghai Peoples R China Shanghai Univ Med & Hlth Sci Sch Med Imaging Shanghai Peoples R China

ISBN: (纸本)9781538676042

In clinical 3D shape of retina often provides more structural information assisting ophthalmologist to diagnosis fundus disease. Shape from shading is one of such approaches able to recover 3D structure of an object and has been used successfully in reconstructing retinal 3D structure from one fundus image. However, it is difficult to evaluate such reconstructed 3D shape because few approaches available to accessing the three-dimensional retinal structure. In this paper, we evaluate 3D reconstruction results by using OCT scan results based on an intensity based registration approach. The experiment result reveals that the reconstructed 3D shape from fundus image has a high coincidence with OCT scan data. And therefore the applicability of three-dimensional reconstruction from the SFS is promising as the 2D fundus images is widely available.

关键词： shape from shading 3D reconstruction image registration OCT image

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Good Neighbors, Bad Neighbors: The Frequent Network Neighborhood Mapping of the Hippocampus Enlightens Several Structural Factors of the Human Intelligence

Good Neighbors, Bad Neighbors: The Frequent Network Neighbor...

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

作者： Mate Fellner Balint Varga Vince Grolmusz PIT Bioinformatics Group Eötvös University Budapest Hungary Uratim Ltd. Budapest Hungary

The human connectome has become the very frequent subject of study of brain-scientists, psychologists and imaging experts in the last decade. With diffusion magnetic resonance imaging techniques, united with advanced data processing algorithms, today we are able to compute braingraphs with several hundred, anatomically identified nodes and thousands of edges, corresponding to the anatomical connections of the brain. The analysis of these graphs without refined mathematical tools is hopeless. These tools need to address the high error rate of the MRI processing workflow, and need to find structural causes or at least correlations of psychological properties and cerebral connections. Until now, structural connectomics was only rarely able of identifying such causes or correlations. In the present work we study the frequent neighbor sets of the most deeply investigated brain area, the hippocampus. By applying the Frequent Network Neighborhood mapping method, we identified frequent neighbor-sets of the hippocampus, which may influence numerous psychological parameters, including intelligence-related ones. Our study utilizes the braingraphs, computed from the imaging data of the Human Connectome Project's 414 subjects, each with 463 anatomically identified nodes.

关键词： Hippocampus Neurons Magnetic resonance imaging Psychology Europe image edge detection

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Evaluation of Low-Contrast Resolution for Computed Tomography by Method of Optimized CNR and Experts' Subjective Evaluation

Evaluation of Low-Contrast Resolution for Computed Tomograph...

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

作者： Chengwei Li Jie Sun Luchen Liu Peng Zhang Wenli Liu Pu Zhang Division of Medical and Biological Measurement National Institute of Metrology Beijing China

This study aimed to optimize the evaluation procedure of contrast to noise ratio (CNR) on low-contrast resolution (LCR) phantom images of computed tomography (CT). Axial CT images of phantom Catphan 600 which contained the low-contrast module CTP515 and the uniformity module CTP486 were acquired from five 64-slices spiral CT scanners with the same scanning parameters. Through conjoint analysis of images of CTP515 and CTP486, two steps of optimization were added to the evaluation procedure to get the optimized CNR results. Meanwhile, four experts were invited to perform the subjective evaluation of the same low-contrast images. With the method of normalization, results gained by optimized CNR and the experts' subjective evaluation were compared to investigate the consistency of the two evaluation methods. According to the comparison of the normalized values, the optimized CNR gained by the method of two-stage average could be used as basis to assist tester achieve similar result compared to that from experts' subjective evaluation.

关键词： Computed tomography Phantoms Noise measurement Imaging phantoms image resolution Metrology Spirals

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GVF and CV Model-based Pulmonary Artery Edge Detection of CTPA image Sequence 11

GVF and CV Model-based Pulmonary Artery Edge Detection of CT...

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11th international congress on image and signal processing, biomedical engineering and informatics (CISP-BMEI)

作者： Guo, Xin Yuan, Hongfang Wen, Zhou Liu, Min Wang, Huaqing Beijing Univ Chem Technol Coll Informat Sci & Technol Beijing Peoples R China China Japan Friendship Hosp Dept Radiol Beijing Peoples R China Beijing Univ Chem Technol Coll Mech & Elect Engn Beijing Peoples R China

ISBN: (纸本)9781538676042

Since the gradient vector flow (GVF) model is not suitable for multi-objects edges detection and cannot adapt to the change of the object's geometric topology, and the Chan-Vese (CV) model is easy to result in false detection, this paper proposes a new method for detecting the edges of the pulmonary artery for the computed tomographic pulmonary angiography (CTPA) image sequences which combines the advantages of GVF model and CV model. Firstly, the initial contour is driven by the GVF field. After getting the converged contour curve, the image inside the curve is extracted;Secondly, CV model-based edge detection is performed on the segmented image to solve the problem of multi-objects detection. Experiments show that the proposed method can effectively solve the problem of pulmonary artery edges detection in CTPA images. Applying the algorithm to targets tracking for image sequence, the method can detect the edges of each target separately, and obtain the independent contours, when the pulmonary artery is split into two.

关键词： Active contour GVF model CV model edge detection CTPA image sequence

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