会议介绍

2019年7月20-22日|中国杭州

2019第三届生物信息与生物医学工程国际学术会议(BIBE 2019)将于2019年7月20-22日在中国杭州召开。

BIBE2019旨在为来自世界各地的专家、学者以及研究人员提供一个良好的交流平台,分享最新研究成果,共同探讨领域内的热门问题,交流新的经验和技术。

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主题演讲人

EEEP2018 | Prof. Chengyu Liu Prof. Chengyu Liu
Southeast University, Nanjing, China
http://ins.seu.edu.cn/2017/0930/c2346a199962/page.htm
Title: Wearable ECG Monitoring
Abstract: Real-time, long-term wearable ECG monitoring is essential for early detecting the cardiovascular diseases and other health risks. This talk presents four important aspects about wearable ECG study, and summarizes the technology challenges exist in each aspect. For hardware, the challenge mainly comes from the textile sensor design and ergonomic design for comfort measurement. Challenges from algorithm aspect include: real-time signal quality assessment, robust&accurate feature detection and big-data&AI-based disease detection model development. High-quality clinical data are also needed, which plays an essential role in training reliable and generalizable models. Herein, the open-access and carefully labeled databases will be starved. Finally, the efficient clinical application is also important, which refers to the specially designed clinical study with the close cooperation with doctors.
EEEP2018 | Prof. Weimin Huang Prof. Weimin Huang
School of Mechanical and Aerospace Engineering, Nanyang Technological University, Singapore
http://www.ntu.edu.sg/home/mwmhuang/
Title: Novel shape memory hydrogels for novel biomedical devices
Abstract: The shape memory effect (SME) enables a nice integration of sensing and actuation together within a piece of material for many novel applications. We have seen a range of biomedical devices utilizing shape memory alloys/polymers. This talk will focus on two new types of shape memory hydrogels, one is water responsive with controlled activation time, and the other is cooling responsive which is ideal for 4D bio-printing. Example biomedical applications of both hydrogels will be demonstrated.
EEEP2018 | Prof. Huiru Zheng Prof. Huiru Zheng
School of Computing, Ulster University, UK
Fellow of Higher Education Academy Senior Member of IEEE
Link: https://www.ulster.ac.uk/staff/h-zheng
Title: From telemedicine to mHealth - sensor enabled applications to support connected health and well-being
Abstract: Telemedicine was originally developed to reach and treat people at remote locations. With the rapid advance of telecommunication, sensors and mobile technology, it has been developed to provide care for people in both rural and urban areas. At the meantime, population ageing has become a global phenomenon and countries are facing ongoing challenges in caring for their elderly. Technologies, especially mobile and wearable technologies, are now available to provide an effective solution for better caring of aging populations to lower healthcare cost. In this talk, Prof. Zheng will highlight recent research work in telecare and mHealth. The application to well-being and self-management of chronic conditions will be presented. The presentation will conclude with the discussion of challenges and opportunities in connected health.
EEEP2018 | Dr. Nidhi Mishra Dr. Nidhi Mishra
Assistant Professor
Indian Institute of Information Technology, Allahabad, India
Title: Advanced Polymeric Biomaterials for Drug Delivery
Abstract: Conventional form of drug delivery is not target specific and the release of drug to the target site is not sustained . Drug delivery via a nanocomposite will give steady and complete drug release. Synthesis and characterization of nanocomposites using polymer matrix of PNIPAM and its use in drug delivery shall be discussed. The synthesis of polymer nanocomposites is an integral aspect of polymer nanotechnology. We have synthesized several nanocomposites using PNIPAM as polymer matrix and other fillers. The synthesized nanocomposites have large surface area per unit volume and interstitial spaces in nanometer range. Thus these are nanocompposites. They have been explored for the application of targeted drug delivery system for anticancer agents.
EEEP2018 | Prof. Jyh-Cheng Chen Prof. Jyh-Cheng Chen
Dept. of Biomedical Imaging & Radiological Sciences National Yang-Ming University
Title: Limited-angle low-dose CT image denoising using wide residual network
Abstract: Dose reduction of the computed tomography (CT) has become a serious issue in the recent radiological studies. In dental digital tomosynthesis (DTS), reconstruction from limited-angle scanning would lead to significant noise and artifacts. In this study, we constructed and validated an image denoising method for limited-angle low-dose CT or DTS images. For the training process, normal-dose DTS (NDDTS) and low-dose DTS (LDDTS) images of human teeth were acquired. We collected the real data with angular coverage of scanning from -60 to 60 degrees, with a sampling interval of one degree as limited-angle data. We also segmented each slice into small patches for training with modified wide residual network (WRN) for image denoising task.s For the streak artifacts reduction, noise reduction, visualization of the tooth structure, our denoising LDDTS images showed significantly better image quality than those of NDDTS images in terms of signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and artifact index as quantitative results. In this work, we trained a modified WRN as an image denoising method for limited-angle LDDTS images. The performance evaluation of the results by visual inspection as well as quantitive measurements shows that our proposed method is comparable to other main stream networks on image denoising.
EEEP2018 | Prof. Chen Bin Prof. Chen Bin
full professor and vice director in State Key Laboratory of Multiphase Flow in Power Engineering, Xi’an Jiaotong University
Title: Intelligent Diagnosis and Personalized Laser Treatment for the Vascular Dermatology Based on the Laser Speckle Imaging.
Abstract: As one of the typical congenital vascular dermatoses caused by dermal capillary malformation, port wine stain (PWS) birthmarks occur in 0.3%–0.5% of newborns, which can negatively affect the physical and mental well-being of patients because 90% of these marks appear on the face and neck. PWS has been demonstrated to be curable by laser-mediated therapies based on the selective photothermolysis. However, the total cute rate was still very low. One important reason of the low cute rate is the poor scalability of the malformed micro vessels, leading to the empirical dependent treatment. Aiming to the precise therapy, the morphological features of blood vessels are important for the evaluation and optimization of the laser parameters. Unfortunately, few effective measurement methods are available for thin skin tissue. A theoretical model used for extracting the optical and structural parameters of tissue medium was developed by integrating the spectral measurement and mathematical method for inverse radiation method. This model was experimentally validated by constructing tissue phantoms and conducting spectral measurements, where good agreement can be observed between the measured and calculated spectroscopic data. The vessel depth extraction procedure was demonstrated in the tissue phantom with a single discrete blood vessel, where the average relative error of estimated vessel depth was only about 5%. Together with the vessel diameter by laser speckle imaging, personalized precise treatment can be expected.
EEEP2018 | Dr.Min Zhao Dr. Min Zhao
University of the sunshine coast
http://www.bioinfo-minzhao.org/index.html
Title: The application of whole exome sequencing to identify the rare variants for clinical practice
Abstract: Recently, evolution of powerful genetic techniques, including whole exome sequencing (WES), has enabled important new discoveries in an array of genetic diseases. However, the large-scale genetic data manipulation and analysis has become a challenge to translate genetic data into the clinical practice. We presented our integrative analysis approaches on two lung diseases (pulmonary arterial hypertension and pulmonary fibrosis) with different strategies to explain how genomics data can help clinical diagnosis and drug use recommendations. Using linkage analysis-based strategy, we employed WES in 190 pulmonary fibrosis families and to date have identified functional rare variants (RVs) associated with telomere function, centrosome function, and various stress-related pathways. In the arterial hypertension study, we performed whole-exome sequencing (WES) on 36 patients and sought to identify RVs underlying IPAH and determine whether RVs differ in vasodilator-responsive patients versus vasodilator-nonresponsive patients. The output from these two studies help us to carry out deep genetic mutation screening and to explore the biological mechanism behind it. The talk will mainly involve the analysis and integration of multi-family genetic disease analysis, the construction and analysis of drug-related genetic networks to accelerate the drug development process. Identifying those disease-causing RVs will clarify critical mechanisms in the pathogenesis of familial disease and sporadic rare diseases.
EEEP2018 | Prof. FangXiang Wu Prof. FangXiang Wu
professor of College of Engineering, and of Department of Computer Science at the University of Saskatchewan, Canada
Title: Machine Learning and Deep Learning Models for Brain Image Analysis
Abstract: Magnetic Resonance Imaging (MRI) is a non-invasive and good soft tissue contrast imaging modality, which provides invaluable information about the brain without exposing objects to a high ionization radiation. However, it is challenging to discover new knowledge such as lesion segmentation and diagnosis of diseases from brain MRI images. In this presentation, I will talk about some of our recent results for analyzing brain MRI images based on machine learning and deep learning models. First, I will present several machine learning models that we developed for diagnosing brain diseases by transferring brain MRI images into brain networks. I will then introduce one deep learning model we developed for segmenting brain disease lesions in brain images.

关于杭州

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杭州,简称“杭”,浙江省省会,钱塘江下游,京杭大运河南端,中国重要的电子商务中心,中国八大古都之一。

杭州风景秀丽,物产丰富,素有“鱼米之乡”“丝绸之府”“人间天堂”的美誉。著名的有龙井茶叶、天竺筷、昌化山核桃、真丝绡、西湖绸伞、古香缎、天目云雾、藕粉、杭州刺绣等等。

杭帮菜隶属中国八大菜系的浙菜,以“清爽别致”闻名,尤其注重一个“鲜”字。由于生活在气候宜人的江南水乡,杭城人口味偏清淡。因此,杭帮菜更注重选料时鲜、保留食材的原汁原味,烹饪时轻油轻调料。鲜咸合一,捎带甜味。宋代大诗人苏东坡曾盛赞“天下酒宴之盛,未有如杭城也”,且有“闻香下马”的典故。

关于旅游

杭州风景秀丽,古迹众多,有大量的自然及人文景观遗迹。其中包括两个国家级风景区,两个国家级自然保护区,七个国家森林公园,一个国家级旅游度假区,首个国家级湿地。

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