2017 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)最新文献_第7页

Development of quantitative index evaluating anticancer or carcinogenic potential of diet: The Anti-Cancer Food Scoring System (ACFS) 1.0 评价饮食抗癌或致癌潜力的定量指标的发展:抗癌食品评分系统(ACFS) 1.0

2017 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) Pub Date : 2017-11-01 DOI: 10.1109/ICIIBMS.2017.8279759

C. H. Rim

引用次数: 0

Ins and outs of dendritic integration in awake mice 清醒小鼠树突整合的来龙去脉

2017 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) Pub Date : 2017-11-01 DOI: 10.1109/ICIIBMS.2017.8279755

Christopher J. Roome, B. Kuhn

{"title":"Ins and outs of dendritic integration in awake mice","authors":"Christopher J. Roome, B. Kuhn","doi":"10.1109/ICIIBMS.2017.8279755","DOIUrl":"https://doi.org/10.1109/ICIIBMS.2017.8279755","url":null,"abstract":"Neurons are frequently viewed as discrete input-output computers; decoding synaptic inputs to their dendrites to generate correct outputs from their soma, through ‘dendritic integration’. Yet fundamental properties, such as spatio-temporal patterns of synaptic inputs, and the number of inputs required to generate an output in awake animals, remain unknown. We combined simultaneous voltage and calcium imaging from spiny dendrites, with somatic electrical recording from cerebellar Purkinje neurons to investigate dendritic integration in awake mice. Here we show spatio-temporal patterns of dendritic signaling and their non-linear relationship with somatic output and provide an estimate for the number of synaptic inputs required to generate a somatic output. Sub-millisecond two-photon imaging detected rapid and localized sub- and supra-threshold dendritic signaling and revealed how high frequency electrical dendritic inputs concurrently regulate somatic output and permit isolated dendritic computations with millisecond precision. These findings explore the complexity of dendritic signaling and support the hypothesis that dendritic processes behave as fundamental computational units.","PeriodicalId":122969,"journal":{"name":"2017 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121503312","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

Autonomous flight drone for infrastructure (transmission line) inspection (3) 用于基础设施(输电线路)巡检的自主飞行无人机(3)

2017 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) Pub Date : 2017-11-01 DOI: 10.1109/ICIIBMS.2017.8279692

M. Morita, Hironobu Kinjo, Shido Sato

引用次数: 12

Artificial neural network based nuclei segmentation on cytology pleural effusion images 基于人工神经网络的胸膜积液细胞学图像核分割

2017 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) Pub Date : 2017-11-01 DOI: 10.1109/ICIIBMS.2017.8279748

Khin Yadanar Win, S. Choomchuay, K. Hamamoto, Manasanan Raveesunthornkiat

{"title":"Artificial neural network based nuclei segmentation on cytology pleural effusion images","authors":"Khin Yadanar Win, S. Choomchuay, K. Hamamoto, Manasanan Raveesunthornkiat","doi":"10.1109/ICIIBMS.2017.8279748","DOIUrl":"https://doi.org/10.1109/ICIIBMS.2017.8279748","url":null,"abstract":"Automated segmentation of cell nuclei is the crucial step towards computer-aided diagnosis system because the morphological features of the cell nuclei are highly associated with the cell abnormality and disease. This paper contributes four main stages required for automatic segmentation of the cell nuclei on cytology pleural effusion images. Initially, the image is preprocessed to enhance the image quality by applying contrast limited adaptive histogram equalization (CLAHE). The segmentation process is relied on a supervised Artificial Neural network (ANN) based pixel classification. Then, the boundaries of the extracted cell nuclei regions are refined by utilizing the morphological operation. Finally, the overlapped or touched nuclei are identified and split by using the marker-controlled watershed method. The proposed method is evaluated with the local dataset containing 35 cytology pleural effusion images. It achieves the performance of 0.95%, 0.86 %, 0.90% and 92% in precision, recall, F-measure and Dice Similarity Coefficient respectively. The average computational time for the entire algorithm took 15 mins per image. To our knowledge, this is the first attempt that utilizes ANN as the segmentation on cytology pleural effusion images.","PeriodicalId":122969,"journal":{"name":"2017 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134246249","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

Emergence of robust cooperative states by iterative internalizations of opponents' personalized values in minority game 少数博弈中对手个性化价值的迭代内化产生稳健合作状态

2017 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) Pub Date : 2017-11-01 DOI: 10.1109/ICIIBMS.2017.8279742

Takashi Sato

引用次数: 3

2-P imaging of mouse visual cortex layer 6 corticothalamic feedback during different behavior states 不同行为状态下小鼠视觉皮层第6层皮质丘脑反馈的二维成像

2017 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) Pub Date : 2017-11-01 DOI: 10.1109/ICIIBMS.2017.8279756

S. Augustinaite, B. Kuhn

{"title":"2-P imaging of mouse visual cortex layer 6 corticothalamic feedback during different behavior states","authors":"S. Augustinaite, B. Kuhn","doi":"10.1109/ICIIBMS.2017.8279756","DOIUrl":"https://doi.org/10.1109/ICIIBMS.2017.8279756","url":null,"abstract":"Layer 6 (L6), the deepest lamina of cerebral cortex, is one of the key structures regulating behavior state related information processing within the cortex and various subcortical areas. However, very little is known about the functional significance of different L6 circuits in vivo. L6 experiments in the behaving animals still remain challenging due to hard access of the recording / imaging site, complexity of neuronal circuits and heterogeneity in neuron morphology. Here, we focus on primary visual cortex L6 feedback projections to visual thalamus (lateral geniculate nucleus) which regulate visual signal transmission from retina to cortex. We developed a method to “dissect” and study these L6 corticothalamic feedback projections in vivo with 2P microscopy. With this method, we can reliably image retrogradely labeled corticothalamic and other excitatory L6 neurons throughout full layer, down to about 850 μm below dura in a head-fixed mouse. Up to a few hundred individual neurons can be recorded simultaneously for several hours and/or repeatedly recorded during different days, while monitoring mouse behavior state. This allows us to study the cortical feedback to the primary visual thalamus during different behavior states, ranging from full alertness to sleep.","PeriodicalId":122969,"journal":{"name":"2017 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"101 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114818297","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

Classification of P300 in EEG signals for disable subjects using singular spectrum analysis 残障受试者脑电信号P300的奇异谱分类

2017 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) Pub Date : 2017-11-01 DOI: 10.1109/ICIIBMS.2017.8279747

H. Tjandrasa, S. Djanali, F. X. Arunanto

{"title":"Classification of P300 in EEG signals for disable subjects using singular spectrum analysis","authors":"H. Tjandrasa, S. Djanali, F. X. Arunanto","doi":"10.1109/ICIIBMS.2017.8279747","DOIUrl":"https://doi.org/10.1109/ICIIBMS.2017.8279747","url":null,"abstract":"Brain-computer interfaces have been enabled severely disabled users to communicate with their environments. One method is to use a controlled stimulus to elicit the P300 event-related potential. EEG signals during the repeated stimuli were recorded from four disabled subjects and processed with a Butterworth bandpass filter and Singular Spectrum Analysis, normalized, separated into 2 groups of the target and non-target trial data, and averaged for every 5 trials for each group before classified using a neural network. The purpose of averaging every five target and non-target trials was to emerge the P300 component of even-related potentials so that the target trials could be differentiated from the non-target trials. Further processing by selecting 1 of every 5 processed non-target trials increased the value of sensitivity by 10.9%, it showed that the number of false negatives of target trials was reduced. The results of the classification gave the maximum accuracy of 92.5%. The average values of sensitivity, specificity, and accuracy were 70.8%, 89,8%, and 84.6% respectively.","PeriodicalId":122969,"journal":{"name":"2017 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS)","volume":"380 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122858040","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

Development of endoscopic system based on fluorescence imaging for detection of colon cancer 基于荧光成像的结肠癌内镜检测系统的研制

2017 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) Pub Date : 2017-11-01 DOI: 10.1109/ICIIBMS.2017.8279732

Kiri Lee, Jiseop Kim, Byungjun Park, H. Bang, Byungyeon Kim, Youngjae Won, Seungrag Lee

引用次数: 0

A medical training system using augmented reality 使用增强现实技术的医疗培训系统

2017 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) Pub Date : 2017-11-01 DOI: 10.1109/ICIIBMS.2017.8279706

Ryosuke Umeda, Mohamed Atef Seif, H. Higa, Yukio Kuniyoshi

引用次数: 11

Behavior analysis of a small animal using IoT sensor system 利用物联网传感器系统对小动物进行行为分析

2017 International Conference on Intelligent Informatics and Biomedical Sciences (ICIIBMS) Pub Date : 2017-11-01 DOI: 10.1109/ICIIBMS.2017.8279686

Asuka Noda, O. Fukuda, H. Okumura, K. Arai

引用次数: 6