2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE)最新文献

{"title":"Automatic Brain Extraction for T1-Weighted Magnetic Resonance Images Using Region Growing","authors":"Yu-Lung Ho, Wei-Yang Lin, Chia-Ling Tsai, Cheng-Chia Lee, Chih-Yang Lin","doi":"10.1109/BIBE.2016.42","DOIUrl":"https://doi.org/10.1109/BIBE.2016.42","url":null,"abstract":"In this paper, we propose a novel method for extracting brain region from T1-weighted magnetic resonance imaging. Our proposed method is based on finding a seed point which is located on brain tissue and then perform region growing. In particular, we firstly analyze intensity distributions of different cerebral tissues (including brain, cerebrospinal fluid, scalp and marrow) at middle height. We also measure the distance from image center to brain edge at the same height of brain scan. In the experimental validation, we have conducted experiment on the OASIS dataset and perform comparison with the state-of-the-art methods. Our propose method achieves the best performance on the OASIS dataset.","PeriodicalId":377504,"journal":{"name":"2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123385278","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}

{"title":"Validity of the Mind Monitoring System as a Mental Health Indicator","authors":"Naoki Hagiwara, Y. Omiya, Shuji Shinohara, M. Nakamura, Masakazu Higuchi, H. Yasunaga, S. Mitsuyoshi, S. Tokuno","doi":"10.1109/BIBE.2016.62","DOIUrl":"https://doi.org/10.1109/BIBE.2016.62","url":null,"abstract":"We have been developing a method to evaluate the mental health condition of a person by the sound of his or her voice. Now, we have applied this technology as a system to create a smartphone app. Since using voice to measure one's mental health condition is a non-invasive method and as it could be used continually through the smartphone, one carries, unlike a routine checkup, it could be used for monitoring on a daily basis. The purpose of this study is to compare this vitality score and the widely used BDI (Beck Depression Inventory) and evaluate its validity. This experiment was conducted at COI (Center of Innovation) Program of the University of Tokyo with a total of 50 employees of multiple corporations as subjects between early December 2015 and early February 2016. The test subjects were each lent a smartphone with our app recording their voices automatically during calls, and in addition to it, we had them read and record a fixed phrase daily. BDI test was conducted at the beginning of the experiment period. The vitality score was calculated based on the voice data collected during the first two weeks of the experiment and considered it the vitality score of the time BDI was conducted. When these two indicators were compared, we found there was a negative correlation between BDI and the vitality score. Additionally, it was a useful method to identify a test subject with a high BDI score.","PeriodicalId":377504,"journal":{"name":"2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128530093","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}

{"title":"Simple and Robust Ideal Mid-Sagittal Line (iML) Extraction Method for Brain CT Images","authors":"Wenbo Li, Haiwei Pan, Xiaoqin Xie, Zhiqiang Zhang, Qilong Han","doi":"10.1109/BIBE.2016.47","DOIUrl":"https://doi.org/10.1109/BIBE.2016.47","url":null,"abstract":"Identification of ideal mid-sagittal line (iML) is important for image registration, brain segmentation, pathology detection and particularly for medical image classification. In this paper, iML extraction method based on scale invariant feature transform (SIFT) features is proposed for brain CT images. The method consists of an offline part and an online part. In the offline part, the iML feature points of training set is extracted by an auxiliary tool and an optimized matching template set is obtained by our feature fusion and filtering algorithms. In the online part, a matching point set is generated by matching SIFT features of test images to the offline template. Then the point set is refined by our pruning algorithm and iMLs of test images are fitted by the refined point set. Both real and simulated image data sets are used to verify the accuracy, robustness and execution efficiency of the algorithm. Experimental results show that, our method achieves good accuracy and efficiency in both real and simulation image sets, and performs better tolerance to rotation, noise, fuzzy and asymmetry in comparison with other existing algorithms.","PeriodicalId":377504,"journal":{"name":"2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"17 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126765650","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}

{"title":"Analyzing Retinal Optical Coherence Tomography Images Using Differential Spatial Pyramid Matching","authors":"P. Chundi, M. Subramaniam, Keivan Sabet, E. Margalit","doi":"10.1109/BIBE.2016.67","DOIUrl":"https://doi.org/10.1109/BIBE.2016.67","url":null,"abstract":"Spatial pyramid matching (SPM) has achieved impressive successes in analyzing and classifying images across several domains. SPM computes a similarity measure over images by using bag of words similarity score over different levels of coarseness of the images. In this paper we propose a novel, simple approach based on SPM, differential SPM (DSPM) that incorporates finer differences among images while determining image similarity. The approach propagates the differences seen at fine levels to dampen the similarity observed at the coarser levels, thereby highlighting differences among images at small, localized regions. The resulting similarity scores among images can better separate images that match at coarse levels, but have subtle differences. DSPM integrated with K-nearest neighbor classification approaches was used to identify and analyze retinal Optical Coherence Tomography (OCT) images containing normal retinal scans as well as those from subjects with AMD (age-related macular degeneration) and DME (diabetic macular edema). The proposed approach achieved higher classification accuracy with smaller training overheads in comparison to SPM in all cases in our experiments.","PeriodicalId":377504,"journal":{"name":"2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"41 4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123075583","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}

{"title":"Development of Multi-scale Musculo-Skeletal Simulator","authors":"N. Yamamura, S. Takagi, T. Nomura","doi":"10.1109/BIBE.2016.34","DOIUrl":"https://doi.org/10.1109/BIBE.2016.34","url":null,"abstract":"This paper presents preliminary status of our project for developing a multi-scale simulation of musculo-skeletal system for providing a useful tool in the field of musculo-skeletal physiology and related healthcare issues. Here, a mechanically and physiologically detailed model of skeletal muscles, as a key building block of the system, is considered, in which hierarchical structure of skeletal muscles is modeled by multiple one-dimensional muscle fiber models embedded in a three-dimensional finite element continuum-mechanics model. For modeling the excitation-contraction coupling, we combined models at multiple scales including electrophysiology for action potential generation in muscle fibers, Ca2+ dynamics of sarcoplasmic reticulum describing calcium release and uptake, and cross-bridge dynamics that can reproduce stochastic cross-bridge kinetics with a state transition model of the myosin molecules via Monte Carlo simulation. We then validated each of these models for the excitation-contraction coupling by comparing dynamics of the models with physiological data available in literatures on the muscle function.","PeriodicalId":377504,"journal":{"name":"2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127734953","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}

{"title":"Genome-Wide Functional Identification of Maximal Consensus Patterns Derived from Multiple Species piRNAs","authors":"Wen-Ling Chan, Mei-Chun Yeh, Jing-doo Wang, Jan-Gowth Chang, J. Tsai","doi":"10.1109/BIBE.2016.65","DOIUrl":"https://doi.org/10.1109/BIBE.2016.65","url":null,"abstract":"Piwi-interacting RNA (piRNA), with 24 to 33 nt, is the largest category of small non-coding RNA (ncRNA) molecules expressed in animal cells. piRNA complexes have been revealed to both epigenetic and post-transcriptional regulation in germ line and somatic tissues. Generally, they are distinct from microRNA (miRNA) in size and lack of sequence conservation. In this study, class frequency distribution identified the consensus patterns of piRNA across 9 species. To analyze the mechanism of these consensus patters, 4 target prediction tools were integrated. Furthermore, the GO-Term and pathway enrichment were approached for the functional annotation of these targets. The results indicated that two maximal conserved patterns of piRNA were identified in 8 species, whereas maximal consensus pattern in all of 9 species was TAGCTCAGTCGGTAGAGCA seemed to regulate many human genes which involved in binding and activity molecular function. Additionally, these target genes are associated with a number of rare diseases. We believe that this study will contribute to a better understanding of the functionality of piRNA cross species conserved sequences.","PeriodicalId":377504,"journal":{"name":"2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130190701","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}

{"title":"Comparative Analysis of Transformation Methods for Gene Expression Profiles in Breast Cancer Datasets","authors":"Yoshiaki Sota, S. Seno, Y. Takenaka, S. Noguchi, H. Matsuda","doi":"10.1109/BIBE.2016.51","DOIUrl":"https://doi.org/10.1109/BIBE.2016.51","url":null,"abstract":"Gene expression profiling has been increasingly used in clinical practice. Integration of expression data across multiple experiments provides better insight into the heterogeneity of the biology being examined. A problem of the data integration, an experimental batch from platform or laboratory sources, remains a barrier to systematically analyzing data across different datasets. Several methods (such as, ComBat) have been proposed to remove batch effects. However, these methods often make assumptions about ideal distribution of the underlying data. Difficulties might be expected when comparing datasets that have fundamentally different (dataset-dependent) distributions. For example, clinical datasets are often collected from patient samples with various disease stages or conditions. Therefore, we have compared several mathematical transformations across many datasets, including the nonparametric Z scaling transformation method (NPZ) we have proposed for clinical use. We selected 2,813 patients with available information on estrogen receptor (ER) status or human epidermal growth factor receptor 2 (HER2) status from 24 Affymetrix HG-U133 (GPL96) or Affymetrix HG-U133 plus 2.0 (GPL570) datasets in the Gene Expression Omnibus database. The microarray expression data were processed with one of the four following methods: Raw (background correction and log transformation only), Microarray Suite 5.0 (MAS5), frozen robust multiarray analysis (fRMA), and radius minimax (RMX). The normalized data were sequentially transformed by using one of the following five methods: untransformed (without transformation), single-array-based transformations (RANK, Z, NPZ, or YuGene). Finally, we compared the ER and HER2 statuses assessed by immunohistochemical (IHC) staining with mRNA expression. We found that single-array-based transformation in addition to normalization improved the concordance rates of the IHC staining. We demonstrated the influence of transformation by using breast cancer samples and showed that adding single-array-based transformations to microarray expression data resulted in stronger correlations with IHC staining.","PeriodicalId":377504,"journal":{"name":"2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"630 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116211674","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}

{"title":"HL7 FHIR Compliant Data Access Model for Maternal Health Information System","authors":"Saadia Ismail, Majed Alshmari, Usman Qamar, Wasi Haider Butt, K. Latif, H. F. Ahmad","doi":"10.1109/BIBE.2016.9","DOIUrl":"https://doi.org/10.1109/BIBE.2016.9","url":null,"abstract":"Effective decision-making to improve healthcare for people depends essentially upon availability of reliable health data. Several developing countries have maternal health indicators lagging behind as compared to international targets set by the UN as Millennium or Sustainable Development Goals. One of the major reasons is poor and non-standardized maternal health record keeping that affect data quality and undermines evidence-based decision making. The aim of this research is the design and development of HL7 FHIR compliant data access model for maintaining maternal health data as FHIR resources to enable effective exchange of health data. The proposed model is implemented as restful web services and data is stored in a NoSQL database for flexibility. To evaluate effectiveness, the system was reviewed by healthcare providers and expectant women. Their feedback highlights the usefulness of the proposed system as compared to traditional record keeping techniques. It is anticipated that the proposed system will lay the foundation of a comprehensive maternal healthcare information system. This shall enable trend analysis for policy-making to help accelerate the efforts for meeting global maternal health targets.","PeriodicalId":377504,"journal":{"name":"2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"38 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116563752","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}

{"title":"CASP3, TP53, and MYC Targeted by Triptolide towards Ovary Induce Female Reproductive Toxicity","authors":"Guang Zheng, Xue Yan, Yun Yang, He Zhang, Hongtao Guo, Junping Zhan, Xiaojuan He","doi":"10.1109/BIBE.2016.11","DOIUrl":"https://doi.org/10.1109/BIBE.2016.11","url":null,"abstract":"Triptolide is an important active compound derived from Chinese herbal medicine Tripterygium wilfordii Hook f. Despite its positive therapeutic effects, the female reproductive toxicity is still blocking its clinical application with its toxicity mechanism is still obscure. In order to tackle the mechanism of female reproductive toxicity, one intuitive approach is to explore the biological molecule network involving targeted proteins and associated ovary expressed proteins. In this study, triptolide's target proteins and their biological functions were analyzed first. Then, focused on the enriched process of negative regulation of cell cycle, targeted proteins, together with proteins expressed in ovary which are contributed in negative regulation of cell cycle were extracted so as to form the female reproductive toxicity molecule network. Finally, three targeted proteins of CASP3, TP53, and MYC were highlighted as the leading causation of female reproductive toxicity. Further analysis indicated that these 3 target proteins can further regulate 21 ovary expressed proteins which also participate in associated processes. This study provides specified molecule level mechanism the female reproductive toxicity of triptolide which can be used to prevent toxicity while keeping its therapeutic effects.","PeriodicalId":377504,"journal":{"name":"2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130878871","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}

{"title":"Workload Induces Changes in Hemodynamics, Respiratory Rate and Heart Rate Variability","authors":"Taishi Nagasawa, H. Hagiwara","doi":"10.1109/BIBE.2016.27","DOIUrl":"https://doi.org/10.1109/BIBE.2016.27","url":null,"abstract":"Advances in image processing mean it is now possible to measure heart rate variability (HRV) and respiratory rate without contact. The influence of mental workload and dual tasking on HRV and respiratory rate has not been well studied. The objective of the present study was to quantify the relations between workload and dual tasking and HRV and respiratory rate. We measured the weighted workload score of the NASA Task Load Index, the mean oxygenated hemoglobin (oxyHb) concentration, the standard deviation of oxyHb concentration, respiratory data and electrocardiogram data. Subjects performed n-back tasks, Stroop tasks and visual search tasks in low-and high-workload conditions and single-and dual-task conditions. Each task required different attention functions. Respiratory rate was significantly greater in the dual-task conditions than in the single-task conditions, indicating that divided attention increased respiratory rate. The NASA Task Load Index weighted workload score in the Stroop task was higher in the high-workload, dual-task condition than in the low-workload or single-task condition, and oxyHb concentration in the frontal area was lower. This indicates an overload state. In this condition, electrocardiogram data showed distinctive trends. For example, the high-frequency component of electrocardiogram data and mean RR interval were high in the high-workload, dual-task condition. These results suggest that attentional functions and overload in a dual task affected respiratory rate and HRV.","PeriodicalId":377504,"journal":{"name":"2016 IEEE 16th International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124100772","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}