2013 Biomedical Sciences and Engineering Conference (BSEC)最新文献

Forewarning of epileptic events from scalp EEG 头皮脑电图对癫痫事件的预警

2013 Biomedical Sciences and Engineering Conference (BSEC) Pub Date : 2013-05-21 DOI: 10.1109/BSEC.2013.6618498

L. Hively, J. McDonald, N. Munro, Emily Cornelius

引用次数: 12

Automated tracing and segmentation tool for migrating neurons in 4D confocal imagery 四维共聚焦图像中迁移神经元的自动跟踪和分割工具

2013 Biomedical Sciences and Engineering Conference (BSEC) Pub Date : 2013-05-21 DOI: 10.1109/BSEC.2013.6618488

M. Karakaya, R. Kerekes, D. Solecki

{"title":"Automated tracing and segmentation tool for migrating neurons in 4D confocal imagery","authors":"M. Karakaya, R. Kerekes, D. Solecki","doi":"10.1109/BSEC.2013.6618488","DOIUrl":"https://doi.org/10.1109/BSEC.2013.6618488","url":null,"abstract":"Accurate tracing and segmentation of subcellular components of migrating neurons in confocal image sequences are prerequisite steps in many neurobiology studies to understand the biological machinery behind the movement of developing neurons. In this paper, we present an automated tracking, tracing, and segmentation tool for soma, leading, and trailing process of migrating neurons in time-lapse image stacks acquired with a confocal fluorescence microscope. In our approach, we first localize each neuron in the maximum intensity projection of the first frame using manual labeling of the soma and end points of the leading and trailing process. By using each soma position at the first frame, we automatically track the somas in rest of the frames. Then, leading and trailing process are traced in each frame from the soma center to the labeled end tip of the process by using fast marching algorithm. Finally, the soma, leading and trailing processes of each neuron are segmented by using the soma center and traces as seed points, and their boundaries are separated from each other. Based on qualitative results, we demonstrate the capability to automatically track, trace, and segment the soma, leading, and trailing processes of a migrating neuron with minimal user input.","PeriodicalId":431045,"journal":{"name":"2013 Biomedical Sciences and Engineering Conference (BSEC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129735733","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

Personalized modeling of human gaze: Exploratory investigation on mammogram readings 人类凝视的个性化建模:乳房x光片读数的探索性研究

2013 Biomedical Sciences and Engineering Conference (BSEC) Pub Date : 2013-05-21 DOI: 10.1109/BSEC.2013.6618495

S. Voisin, Hong-Jun Yoon, G. Tourassi, Garnetta Morin-Ducote, K. Hudson

{"title":"Personalized modeling of human gaze: Exploratory investigation on mammogram readings","authors":"S. Voisin, Hong-Jun Yoon, G. Tourassi, Garnetta Morin-Ducote, K. Hudson","doi":"10.1109/BSEC.2013.6618495","DOIUrl":"https://doi.org/10.1109/BSEC.2013.6618495","url":null,"abstract":"Eye tracking studies in medical imaging typically focus on studying radiologists' visual search process and how it relates to the clinical interpretation task at hand. In this pilot study, we have investigated gaze patterns to gain insight into their association with radiologists' expertise level as well as the presence of individual differences to facilitate personalized modeling and recognition of radiologists. First, we collected gaze data from six radiologists viewing 40 mammographic images each. Then, the collected gaze data were analyzed with two different approaches: 1) using a multilayer perceptron and 2) using a hidden Markov model. Both approaches confirmed that the experience level of a radiologist can be inferred with high accuracy by simply studying their gaze pattern. Personalized modeling and identification of radiologists was successful with both approaches with accuracy significantly higher than random guessing. The results of this pilot study confirm that a radiologist's perceptual behavior is not only a function of clinical training and level of experience, but there are individual aspects that could serve as a personal biomarker when developing models of human perception and cognition in medical image interpretation.","PeriodicalId":431045,"journal":{"name":"2013 Biomedical Sciences and Engineering Conference (BSEC)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130484935","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: 3

Inferring biochemical routes from biochemical networks 从生化网络推断生化路线

2013 Biomedical Sciences and Engineering Conference (BSEC) Pub Date : 2013-05-21 DOI: 10.1109/BSEC.2013.6618500

Soma Ghosh, S. Vishveshwara, N. Chandra

引用次数: 0

Computational framework to integrate the effect of antigen recognition on disease epidemiology outcome: Multi-scale approach 整合抗原识别对疾病流行病学结果影响的计算框架:多尺度方法

2013 Biomedical Sciences and Engineering Conference (BSEC) Pub Date : 2013-05-21 DOI: 10.1109/BSEC.2013.6618501

S. Mukherjee, N. Chandra

{"title":"Computational framework to integrate the effect of antigen recognition on disease epidemiology outcome: Multi-scale approach","authors":"S. Mukherjee, N. Chandra","doi":"10.1109/BSEC.2013.6618501","DOIUrl":"https://doi.org/10.1109/BSEC.2013.6618501","url":null,"abstract":"Human Leukocyte Antigen (HLA) plays an important role, in presenting foreign pathogens to our immune system, there by eliciting early immune responses. HLA genes are highly polymorphic, giving rise to diverse antigen presentation capability. An important factor contributing to enormous variations in individual responses to diseases is differences in their HLA profiles. The heterogeneity in allele specific disease responses decides the overall disease epidemiological outcome. Here we propose an agent based computational framework, capable of incorporating allele specific information, to analyze disease epidemiology. This framework assumes a SIR model to estimate average disease transmission and recovery rate. Using epitope prediction tool, it performs sequence based epitope detection for a given the pathogenic genome and derives an allele specific disease susceptibility index depending on the epitope detection efficiency. The allele specific disease transmission rate, that follows, is then fed to the agent based epidemiology model, to analyze the disease outcome. The methodology presented here has a potential use in understanding how a disease spreads and effective measures to control the disease.","PeriodicalId":431045,"journal":{"name":"2013 Biomedical Sciences and Engineering Conference (BSEC)","volume":"3 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115002335","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

MRI-based diagnostic system for early detection of prostate cancer 基于mri的前列腺癌早期诊断系统

2013 Biomedical Sciences and Engineering Conference (BSEC) Pub Date : 2013-05-21 DOI: 10.1109/BSEC.2013.6618490

A. Firjani, Adel Said Elmaghraby, A. El-Baz

引用次数: 11

Developing in vitro models of the sub-retinal microenvironment 视网膜下微环境体外模型的建立

2013 Biomedical Sciences and Engineering Conference (BSEC) Pub Date : 2013-05-21 DOI: 10.1109/BSEC.2013.6618483

Elizabeth Vargis, C. Foster, Cristen B. Peterson, J. Morrell-Falvey, S. Retterer, C. Collier

引用次数: 0

Scalp EEG signal reconstruction for detection of mild cognitive impairment and early Alzheimer's disease 头皮脑电图信号重建对轻度认知障碍和早期阿尔茨海默病的检测

2013 Biomedical Sciences and Engineering Conference (BSEC) Pub Date : 2013-05-21 DOI: 10.1109/BSEC.2013.6618497

J. McBride, Xiaopeng Zhao, N. Munro, Yang Jiang, Charles D. Smith, G. Jicha

{"title":"Scalp EEG signal reconstruction for detection of mild cognitive impairment and early Alzheimer's disease","authors":"J. McBride, Xiaopeng Zhao, N. Munro, Yang Jiang, Charles D. Smith, G. Jicha","doi":"10.1109/BSEC.2013.6618497","DOIUrl":"https://doi.org/10.1109/BSEC.2013.6618497","url":null,"abstract":"Mild cognitive impairment (MCI) is a neurological disease which is often comorbid with early stages of Alzheimer's disease (AD). This study explores the potential for detecting changes in neurological functional organization which may be indicative of MCI and early AD using neural network models for scalp EEG signal reconstruction. Resting 32-channel EEG records from 48 age-matched participants (mean age 75.7 years)-15 normal controls (NC), 16 MCI, and 17 early-stage AD-are examined. Neural network models are trained to reconstruct artificially “deleted” samples of EEG using subsets of records from NC participants. Models are applied to EEG records and quality scores are assigned to reconstructions of individual channels. Principal components of regional average reconstruction quality scores are used in a support vector machine model to discriminate between groups. Analyses demonstrate accuracies of 90.3% for MCI vs. NC (p-value<;0.0005), 90.6% for AD vs. NC (p-value<;0.0003), and 87.5% for AD/MCI vs. NC (p-value<;0.0003). Techniques developed here may be used to detect changes in EEG activity due to neurological degeneration associated with MCI and early AD.","PeriodicalId":431045,"journal":{"name":"2013 Biomedical Sciences and Engineering Conference (BSEC)","volume":"141 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2013-05-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124483679","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: 3

Prediction of ICU in-hospital mortality using a deep Boltzmann machine and dropout neural net 基于深度玻尔兹曼机和dropout神经网络的ICU住院死亡率预测

2013 Biomedical Sciences and Engineering Conference (BSEC) Pub Date : 2013-05-21 DOI: 10.1109/BSEC.2013.6618491

Daniel Ryan, B. Daley, Kwai L. Wong, Xiaopeng Zhao

引用次数: 6

Acceleration of kaczmarz using orthogonal subspace projections 利用正交子空间投影的kaczmarz加速度

2013 Biomedical Sciences and Engineering Conference (BSEC) Pub Date : 2013-05-21 DOI: 10.1109/BSEC.2013.6618494

T. Wallace, A. Sekmen

引用次数: 5