2014 21th Iranian Conference on Biomedical Engineering (ICBME)最新文献_第7页

Mandibular canal segmentation using 3D Active Appearance Models and shape context registration 下颌管分割使用三维主动外观模型和形状上下文配准

2014 21th Iranian Conference on Biomedical Engineering (ICBME) Pub Date : 2014-11-01 DOI: 10.1109/ICBME.2014.7043884

F. Abdolali, R. Zoroofi

引用次数: 7

Detection of fast ripples using Hidden Markov Model 基于隐马尔可夫模型的快速波纹检测

2014 21th Iranian Conference on Biomedical Engineering (ICBME) Pub Date : 2014-11-01 DOI: 10.1109/ICBME.2014.7043949

F. Nazarimehr, N. Montazeri, M. Shamsollahi, A. Kachenoura, F. Wendung

引用次数: 3

Recognition of emotional states induced by music videos based on nonlinear feature extraction and SOM classification 基于非线性特征提取和SOM分类的音乐视频情绪状态识别

2014 21th Iranian Conference on Biomedical Engineering (ICBME) Pub Date : 2014-11-01 DOI: 10.1109/ICBME.2014.7043946

S. Hatamikia, A. Nasrabadi

{"title":"Recognition of emotional states induced by music videos based on nonlinear feature extraction and SOM classification","authors":"S. Hatamikia, A. Nasrabadi","doi":"10.1109/ICBME.2014.7043946","DOIUrl":"https://doi.org/10.1109/ICBME.2014.7043946","url":null,"abstract":"This research aims at investigating the relationship between Electroencephalogram (EEG) signals and human emotional states. A subject-independent emotion recognition system is proposed using EEG signals collected during emotional audio-visual inductions to classify different classes of continuous valence-arousal model. First, four feature extraction methods based on Approximate Entropy, Spectral entropy, Katz's fractal dimension and Petrosian's fractal dimension were used; then, a two-stage feature selection method based on Dunn index and Sequential forward feature selection algorithm (SFS) algorithm was used to select the most informative feature subsets. Self-Organization Map (SOM) classifier was used to classify different emotional classes with the use of 5-fold cross-validation. The best results were achieved using combination of all features by average accuracies of %68.92 and %71.25 for two classes of valence and arousal, respectively. Furthermore, a hierarchical model which was constructed of two classifiers was used for classifying 4 emotional classes of valence and arousal levels and the average accuracy of %55.15 was achieved.","PeriodicalId":434822,"journal":{"name":"2014 21th Iranian Conference on Biomedical Engineering (ICBME)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123936465","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 27

Automatic segmentation of breast and fibroglandular tissue in breast MRI using local adaptive thresholding 基于局部自适应阈值的乳腺MRI中乳腺和纤维腺组织的自动分割

2014 21th Iranian Conference on Biomedical Engineering (ICBME) Pub Date : 2014-11-01 DOI: 10.1109/ICBME.2014.7043920

Aida Fooladivanda, S. B. Shokouhi, N. Ahmadinejad, M. Mosavi

{"title":"Automatic segmentation of breast and fibroglandular tissue in breast MRI using local adaptive thresholding","authors":"Aida Fooladivanda, S. B. Shokouhi, N. Ahmadinejad, M. Mosavi","doi":"10.1109/ICBME.2014.7043920","DOIUrl":"https://doi.org/10.1109/ICBME.2014.7043920","url":null,"abstract":"Breast density is considered as an important risk factor associated with the development of breast cancer. Breast and fibroglandular tissue segmentation is the main step to compute breast density in Magnetic Resonance Imaging (MRI). This study presents an automatic algorithm to segment breast and fibroglandular tissue in MRI. It is a difficult task due to bias field and similar signal intensity between fibroglandular tissue and pectoral muscle. Our proposed segmentation approach has been developed based on the local adaptive thresholding to dominate on intensity inhomogeneity due to bias field and the low contrast intensity of the boundary between breast and pectoral muscle. The presented approach is validated with a dataset of 2520 bilateral axial breast MR images from 45 women that include all of Breast Imaging Reporting and Data System (BI-RADS) breast density range. Five quantitative metrics as Dice Similarity Coefficient (DSC), Jaccard Coefficient (JC), total overlap, False Negative (FN) and False Positive (FP) are employed to compare similarity between manual and automatic segmentations. For breast segmentation, the presented approach achieves DSC, JC, total overlap, FN and FP values of 0.90, 0.82, 0.89, 0.1 and 0.09, respectively. For fibroglandular tissue segmentation, we attain DSC, JC, total overlap, FN and FP values of 0.96, 0.94, 0.98, 0.02 and 0.04, respectively.","PeriodicalId":434822,"journal":{"name":"2014 21th Iranian Conference on Biomedical Engineering (ICBME)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116332434","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 12

Development of a low-cost profile scanner using DVD pickup head and CCD image sensor 采用DVD拾取头和CCD图像传感器的低成本轮廓扫描仪的研制

2014 21th Iranian Conference on Biomedical Engineering (ICBME) Pub Date : 2014-11-01 DOI: 10.1109/ICBME.2014.7043924

V. Karbasi, N. Abolfathi, S. A. Hashemi, S. Ahmadinia

{"title":"Development of a low-cost profile scanner using DVD pickup head and CCD image sensor","authors":"V. Karbasi, N. Abolfathi, S. A. Hashemi, S. Ahmadinia","doi":"10.1109/ICBME.2014.7043924","DOIUrl":"https://doi.org/10.1109/ICBME.2014.7043924","url":null,"abstract":"This paper provides a new method of using precise and low-cost measurement apparatus for profile scanning of micron scale surfaces and optimistically will be of great use in bio medical engineering applications. The main part of this instrument is an optical pickup head used in DVD drivers consisting of a laser diode source and some optical components gathering in a package together. The most essential novelty of the paper is combination of a CCD image sensor with DVD pickup head instead of photo-detector IC, so it provides us with precise images of the light reflected by the micron scale surfaces. By the way in spite of most of previous studies there's no need to have a perfectly polished samples to have appropriate scanning process. That's all because of high sensitive characteristic of CCD sensors so it's possible to take images even with the least amount of reflected light. Followed by image processing methods desirable information about surface profile is obtained. A calibration curve is resulted by calibration test that creates the last level measuring information of surface profile. The experimental results were compared with SEM images of the sample and a reasonable agreement was observed.","PeriodicalId":434822,"journal":{"name":"2014 21th Iranian Conference on Biomedical Engineering (ICBME)","volume":"298 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122318855","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 2

Long-term prediction of blood pressure time series using multiple fuzzy functions 利用多重模糊函数长期预测血压时间序列

2014 21th Iranian Conference on Biomedical Engineering (ICBME) Pub Date : 2014-11-01 DOI: 10.1109/ICBME.2014.7043906

R. Abbasi, M. Moradi, Seyyedeh Fatemeh Molaeezadeh

{"title":"Long-term prediction of blood pressure time series using multiple fuzzy functions","authors":"R. Abbasi, M. Moradi, Seyyedeh Fatemeh Molaeezadeh","doi":"10.1109/ICBME.2014.7043906","DOIUrl":"https://doi.org/10.1109/ICBME.2014.7043906","url":null,"abstract":"Long-term prediction of mean arterial blood pressure (MAP) time series can help clinicians to select a proper treatment based on their diagnosis. In this way, this paper firstly introduces a new prediction method for time series prediction based on fuzzy functions (FF) in multi-model mode and applies it for forecasting MAP time series as a new application. The proposed model consists of three steps. First step is to estimate the missing values in MAP time series by a linear interpolation method and to denoise it by using the empirical mode decomposition (EMD) procedure. Second step is to reconstruct the phase space. Last step is to apply a predictive model based on fuzzy functions (FFs). This model consists of two parts: 1) identifying the model structure by Gustafson-Kessel (GK) clustering and 2) estimating the output of each cluster by multivariate adaptive regression splines (MARS). Results show that, the proposed FF-based MARS model is more accurate than ANFIS and FF-based ANFIS, and its results are in the range of standard values. Beside, by using different strategies for long-term prediction, multiple FF-based MARS models has best result in comparison to recursive and multiple-recursive strategies.","PeriodicalId":434822,"journal":{"name":"2014 21th Iranian Conference on Biomedical Engineering (ICBME)","volume":"23 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117014449","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 10

Finite element study of lumbar section before and after disc arthroplasty with disc implant (SB Charite III) in comparison to PEEK twin peaks lumbar cage 与PEEK双峰腰椎笼相比，椎间盘置换术(SB Charite III)前后腰椎截面的有限元研究

2014 21th Iranian Conference on Biomedical Engineering (ICBME) Pub Date : 2014-11-01 DOI: 10.1109/ICBME.2014.7043915

N. Soltani, N. Jamshidi, H. Katouzian

{"title":"Finite element study of lumbar section before and after disc arthroplasty with disc implant (SB Charite III) in comparison to PEEK twin peaks lumbar cage","authors":"N. Soltani, N. Jamshidi, H. Katouzian","doi":"10.1109/ICBME.2014.7043915","DOIUrl":"https://doi.org/10.1109/ICBME.2014.7043915","url":null,"abstract":"Nowadays, primary disc degeneration and herniation are treated with total disc replacement. Arthroplasty of degenerated intervertebral disc is alternative to arthrodesis. A successful total disc arthroplasty requires estimating biomechanical behaviors of lumbar section after disc replacement. To achieve an acceptable range of motion for lumbar section, optimum design of intervertebral disc had to be considered. 3D model of an L3-L4 section, based on CT images, was developed using MIMICS software, then the model analyzed by ABAQUS software. In order to show effectiveness of SB ChariteIII behavior, other two model's considering disc fusion and lumbar with intact disc were created. Two disc implants were modelled and assembled with the vertebral segment to simulate disc arthroplasty. Another model with an intact disc was also analyzed for comparison. In this study, design of SB Charitelll with polyethylene core has been used and mechanical behavior of a lumbar vertebral was analyzed. Effects of clinically approved disc implant investigated in comparison to the Intervertébral cage one.","PeriodicalId":434822,"journal":{"name":"2014 21th Iranian Conference on Biomedical Engineering (ICBME)","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129174151","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Simultaneous arm joint angles and force changes in writer's cramp 作家痉挛时手臂关节角度和力的同步变化

2014 21th Iranian Conference on Biomedical Engineering (ICBME) Pub Date : 1900-01-01 DOI: 10.1109/ICBME.2014.7043927

Mehdi Delrobaei, M. Jog, Mallory Jackman, Fariborz Rahimi, S. F. Atashzar, M. Shahbazi, Rajni V. Patel

引用次数: 0

Automatic classification of Alzheimer's disease with resting-state fMRI and graph theory 基于静息状态fMRI和图论的阿尔茨海默病自动分类

2014 21th Iranian Conference on Biomedical Engineering (ICBME) Pub Date : 1900-01-01 DOI: 10.1109/ICBME.2014.7043931

A. Khazaee, A. Ebrahimzadeh, A. Babajani-Feremi

{"title":"Automatic classification of Alzheimer's disease with resting-state fMRI and graph theory","authors":"A. Khazaee, A. Ebrahimzadeh, A. Babajani-Feremi","doi":"10.1109/ICBME.2014.7043931","DOIUrl":"https://doi.org/10.1109/ICBME.2014.7043931","url":null,"abstract":"Study of brain network on the basis of resting-state functional magnetic resonance imaging (fMRI) has provided promising results to investigate changes in connectivity among different brain regions because of diseases. In this study, we combine graph theoretical approaches with advanced machine learning methods to study functional brain network alteration in patients with Alzheimer's disease (AD). Support vector machine (SVM) was used to explore the ability of graph measures in diagnosis of AD. We applied our method on the resting-state fMRI data of twenty patients with AD and twenty age and gender matched healthy subjects. After preprocessing of data, signals from 90 brain regions, segmented based on the automated anatomical labeling (AAL) atlas, were extracted and edges of the graph were calculated using the correlation between the signals of all pairs of the brain regions. Then a weighted undirected graph was constructed and graph measures were calculated. Fisher score feature selection algorithm were employed to choose most significant features. Finally, using the selected features, we were able to accurately classify patients with AD from healthy control ones with accuracy of 97.5%. Results of this study show that pattern recognition and graph of brain network, on the basis of the resting state fMRI data, can efficiently assist in the diagnosis of AD.","PeriodicalId":434822,"journal":{"name":"2014 21th Iranian Conference on Biomedical Engineering (ICBME)","volume":" 6","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132124576","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8