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IEEE International Symposium on biomedical Imaging

作者： Marios A. Gavrielides Hela Masmoudi Nicholas Petrick Kyle J. Myers Stephen M. Hewitt Center for Devices and Radiological Health CDRH Laboratory for the Assessment of Medical Imaging Systems U.S Food and Drug Administration National Institute of Biomedical Imaging and BioEngineering Silver Spring MD USA U.S Food and Drug Administration Laboratory for the Assessment of Medical Imaging Systems Silver Spring MD U.S.A Department of Electrical and Computer Engineering The George Washington University Washington DC U.S.A Tissue Array Research Program National Institutes of Health MD U.S.A

HER-2/neu (HER2) has been shown to be a valuable biomarker for breast cancer. However, inter-observer variability has been reported in the evaluation of HER2 with immunohistochemistry. It has been suggested that automated computer-based evaluation can provide a consistent and objective measure of HER2 expression. In this manuscript, we present an automated method for the quantitative assessment of HER2 using digital microscopy. The method employs imaging algorithms on whole slide images of tissue specimens for the extraction of two features describing HER2 membrane staining, namely membrane staining completeness and membrane staining intensity. A classifier was trained to merge the extracted features into an overall slide assessment score. Preliminary results showed good agreement with the provided truth. The developed automated method has the potential to be used as a computer aid for the immunohistochemical evaluation of HER2 expression with the objective of increasing observer reproducibility.

关键词： Breast cancer Microscopy Biomembranes Immune system Biomarkers Medical treatment biomedical imaging Clustering algorithms Cells (biology) Feature extraction

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Cooperative university/industry development of a freshman 'introduction to ECE design' course

Cooperative university/industry development of a freshman 'i...

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114th Annual ASEE Conference and Exposition, 2007

作者： Williams, Douglas Butera, Robert Uluagac, Selcuk Clark, Matthew Deck, Andy Torba, Michael Trahan, Steven Georgia Institute of Technology United States Undergraduate Affairs School of Electrical and Computer Engineering Georgia Tech. Georgia Department of Electrical and Computer Engineering Interdisciplinary Bioengineering Graduate Program Georgia Tech. United States Georgia Tech. School of Electrical and Computer Engineering United States National Instruments National Instruments Austin TX United States

Faculty members from Georgia Tech's School of electrical and computer engineering (ECE) have worked jointly with engineers from National Instruments (NI) to develop a new freshman engineering course. This course is entitled 'Introduction to ECE Design' and is constructed around the use of the LEGO MINDSTORMS NXT robotics system. NI partnered with LEGO to jointly develop the programming software for the MINDSTORMS NXT, and their engineers are uniquely positioned to provide insight into the use and functionality of these kits. NI engineers have not only provided technical support but have also conceived and designed most of the laboratories for the course. This course addresses the diverse objectives of providing students with a systems-level design experience at the beginning of their academic programs and introducing them to a broad range of ECE disciplines. A primary goal is to enable students to make better-informed decisions when choosing whether or not to major in electrical engineering or computer engineering. © American Society for engineering Education, 2007.

关键词： Systems engineering

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Decision fusion of circulating markers for breast cancer detection in premenopausal women

Decision fusion of circulating markers for breast cancer det...

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7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE

作者： Jesneck, Jonathan L. Mukherjee, Sayan Nolte, Loren W. Lokshin, Anna E. Marks, Jeffrey R. Lo, Joseph Department of Biomedical Engineering Department of Statistical Science Computational Biology and Bioinformatics Program Duke Advanced Imaging Labs. Institute for Genome Sciences and Policy Department of Computer Science Duke University Department of Electrical and Computer Engineering Division of Hematology/Oncology University of Pittsburgh School of Medicine University of Pittsburgh Cancer Institute Pittsburgh PA 15213 United States Department of Experimental Surgery Duke University Medical Center Medical Physics Graduate Program Duke University Durham NC 27708 United States

ISBN: (纸本)1424415098

Current mammographic screeningfor breast cancer is less effective for younger women. To complement mammography for premenopausal women, we investigated the feasibility screening test using 98 blood serum proteins. Because the data set was very noisy and contained only weak features, we used a classifier designed for noisy data: decision fusion. Decision fusion outperformed both a support vector machine (SVM) and linear regression with forward stepwise feature selection on all three two-class classification tasks: normal tissue vs. cancer, normal tissue vs. benign lesions, and benign lesions vs. cancer. Decision fusion detected cancer moderately well (AUC=0.84 on normal vs. cancer), demonstrating promise as a screening tool. Decision fusion also detected benign lesions similarly well (AUC=0.83 on normal vs. benign lesions) and was the only classifier to achieve any success in separating benign from malignant lesions (AUC=0.64 on benign vs. cancer). The classification results suggest that the assayed proteins are more indicative of a secondary effect, such as immune response, rather than specific for breast cancer. In conclusion, the decision fusion classifier demonstrated some promise in detecting breast lesions and outperformed other classifiers, especially for the very noisy classification problem of distinguishing benign from malignant lesions. ©2007 IEEE.

关键词： Tissue

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Contributors to the Lab on a Chip cell and tissue engineering in microsystems special issue

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Lab on a Chip 2007年第6期7卷 667-671页

作者： Bhatia, Sangeeta N. Chen, Christoper Bashir, Rashid Beebe, David J. Desai, Tejal Gottwald, Eric Khademhosseini, Ali Langer, Robert S. Piel, Matthieu Takayama, Shuichi Thorsen, Todd Tien, Joe Voldman, Joel Vunjak-Novakovic, Gordana Wu, Mingming Yu, Hanry Massachusetts Institute of Technology Harvard-MIT Division of Health Sciences and Technology Department of Electrical Engineering and Computer Science United States Laboratory for Multiscale Regenerative Technologies United States Department of Innovation University of Pennsylvania Department of Bioengineering United States Cell Biology and Physiology Program Cell Growth and Cancer Program Tissue Microfabrication Laboratory Department of Electrical and Computer Engineering and Biomedical Engineering Purdue University United States Department of Electronics University of Glasgow United Kingdom Department of Physiology and Bioengineering University of California San Francisco CA United States California Institute for Quantitative Biomedical Research UCSF/UC Berkeley Graduate Group in Bioengineering United States Laboratory of Therapeutic Micro and Nanotechnology Institute for Biological Interfaces Germany 3D-Cell Culture Techniques Group Institute for Biological Interfaces Germany Department of Medicine and Health Sciences and Technology Massachusetts Institute of Technology (MIT) United States Institut Curie UMR 144 IC/CNRS France Biomedical Engineering Department University of Michigan United States Department of Biomedical Engineering Macromolecular Science and Engineering Program United States Sibley School of Mechanical and Aerospace Engineering School of Chemical and Molecular Engineering Cornell University United States National University of Singapore Singapore Institute of Bioengineering and Nanotechnology A STAR Singapore

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Enhancement of information transmission with stochastic resonance in hippocampal CA1 neuron models: Effects of noise input location

Enhancement of information transmission with stochastic reso...

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29th Annual International Conference of IEEE-EMBS, engineering in Medicine and Biology Society, EMBC'07

作者： Kawaguchi, Minato Mino, Hiroyuki Durand, Dominique M. IEEE Graduate School of Engineering Kanto Gakuin University 1-50-1 Mutsuura E. Kanazawa-ku Yokohama 236-8501 Japan Department of Electrical and Computer Engineering Kanto Gakuin University 1-50-1 Mutsuura E. Kanazawa-ku Yokohama 236-8501 Japan Neural Engineering Center Department of Biomedical Engineering Case Western Reserve University 10900 Euclid Ave. Cleveland OH 44106-7207 United States

ISBN: (纸本)1424407885

Stochastic resonance (SR) has been shown to enhance the signal to noise ratio or detection of signals in neurons. It is not yet clear how this effect of SR on the signal to noise ratio affects signal processing in neural networks. In this paper, we investigate the effects of the location of background noise input on information transmission in a hippocampal CA1 neuron model. In the computer simulation, random sub-threshold spike trains (signal) generated by a filtered homogeneous Poisson process were presented repeatedly to the middle point of the main apical branch, while the homogeneous Poisson shot noise (background noise) was applied to a location of the dendrite in the hippocampal CA1 model consisting of the soma with a sodium, a calcium, and five potassium channels. The location of the background noise input was varied along the dendrites to investigate the effects of background noise input location on information transmission. The computer simulation results show that the information rate reached a maximum value for an optimal amplitude of the background noise amplitude. It is also shown that this optimal amplitude of the background noise is independent of the distance between the soma and the noise input location. The results also show that the location of the background noise input does not significantly affect the maximum values of the information rates generated by stochastic resonance. ©2007 IEEE.

关键词： Information dissemination

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Several erythematous papules with a 1.5-cm sized nodule scattering on the face of an old woman

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Dermatologica Sinica 2007年第2期25卷 175-176页

作者： Wang, Shiou-Han Tsai, Tsen-Fang Department of Dermatology National Taiwan University Hospital Taiwan College of Medicine National Taiwan University Taiwan Graduate Institute of Biomedical Electronics and Bioinformatics College of Electrical Engineering and Computer Science National Taiwan University Taiwan Department of Dermatology National Taiwan University Hospital Taipei 100 7 Chung-Shan South Road Taiwan

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Middleware based inpatient healthcare information system

Middleware based inpatient healthcare information system

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7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE

作者： Hsieh, S.H. Hsieh, S.L. Weng, Y.C. Yang, T.H. Lai, Feipei Cheng, P.H. Ping, X.O. Jan, M.Y. Lin, J.C. Peng, C.H. Huang, K.H. Ko, L.F. Chen, C.H. Hsu, K.P. Information Systems Office National Taiwan University Hospital Taipei Taiwan Department of Computer Science and Information Engineering National Taiwan University Taipei Taiwan Department of Electrical Engineering National Taiwan University Taipei Taiwan Network and Computer Centre National Chiao Tung University Hsin Chu Taiwan Graduate Institute of Biomedical Electronics and Bioinformatics National Taiwan University Taiwan Department of Information Management National Taiwan University Taipei Taiwan

ISBN: (纸本)1424415098

The paper presents a multi-tier, integrated, distributed, Inpatient Healthcare Information System based on Service Oriented Architecture (SOA) .NET environment in National Taiwan University Hospital (NTUH). The architecture and outcomes of the newly developed Inpatient Information System (IIS) platform are discussed in details. We also present mechanisms of integration as well as interoperability among the components and multi-database in IIS via Health Level Seven (HL7) Middleware layer. The preliminary performance of the current operating IIS is evaluated and analyzed to verify the efficiency and effectiveness of the architecture we designed. ©2007 IEEE.

关键词： Information systems

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A comparison between traditional shift-and-add (SAA) and point-by-point back projection (BP) - Relevance to morphology of microcalcifications for isocentric motion in Digital Breast tomosynthesis (DBT)

A comparison between traditional shift-and-add (SAA) and poi...

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7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE

作者： Chen, Ying Lo, Joseph Y Dobbins III, James T. Department of Electrical and Computer Engineering Southern Illinois University Carbondale Carbondale IL 62901 United States Department of Biomedical Engineering Duke University Duke University Medical Center Durham NC 27710 United States Duke Advanced Imaging Laboratories Duke University Duke University Medical Center Durham NC 27710 United States Medical Physics Graduate Program Duke University Duke University Medical Center Durham NC 27710 United States

ISBN: (纸本)1424415098

Digital breast tomosynthesis (DBT) is a three-dimensional imaging technique providing an arbitrary set of reconstruction planes in the breast with limited series of projection images. This paper describes a comparison between traditional shift-and-add (SAA) and point-by-point back projection (BP) algorithms by impulse response and modulation transfer function (MTF) analysis. Due to the partial isocentric motion of the x-ray tube in DBT, structures such as microcalcifications appear slightly blurred in traditional shift-and-add (SAA) images in the direction perpendicular to the direction of tube 's motion. Point-by-point BP improved rendition of microcalcifications. The sharpness and morphology of calcifications were improved in a human subject images. A Filtered Back Projection (FBP) deblurring approach was used to demonstrate deblurred point-by-point BP tomosynthesis images. The point-by-point BP rather than traditional SAA should be considered as the foundation of further deblurring algorithms for DBT reconstruction. ©2007 IEEE.

关键词： Impulse response

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New Neurofuzzy Training Procedure Based on Participatory Learning Paradigm

New Neurofuzzy Training Procedure Based on Participatory Lea...

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IEEE International Conference on Fuzzy Systems (FUZZ-IEEE)

作者： Michel Hell Pyramo Costa Fernando Gomide Department of Computer Engineering and Automation (DCA) Faculty of Electrical and Computer Engineering (FEEC) State University of Campinas Sao Paulo Brazil Graduate Program in Electrical Engineering Pontifical Catholic University of Minas Gerais Belo Horizonte Minas Gerais Brazil

In this paper we introduce a new approach to train neurofuzzy networks using the participatory learning concept. The participatory learning paradigm tends to emulate the human learning mechanism where an acceptance mechanism determines which observation is used for learning based upon their compatibility with the current beliefs. The performance of the proposed learning scheme is illustrated by an example involving a nonlinear system modeling problem: the thermal modeling of power transformers. Comparisons with other methods reported in the literature and between two dual network structures are also included. The experimental results show the effectiveness of participatory learning in neurofuzzy networks training.

关键词： Power system modeling Fuzzy systems Power transformers Training data Humans Nonlinear systems Neural networks Fuzzy sets Power engineering computing Power engineering and energy

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Enhancement of Information Transmission with Stochastic Resonance in Hippocampal CA1 Neuron Models: Effects of Noise Input Location

Enhancement of Information Transmission with Stochastic Reso...

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29th Annual International Conference of the IEEE engineering in Medicine and Biology Society (EMBS 2007), vol.16

作者： Minato Kawaguchi Hiroyuki Mino Dominique M. Durand Graduate School of Engineering Kanto Gakuin University Yokohama Japan Department of Electrical and Computer Engineering Kanto Gakuin University Yokohama Japan Neural Engineering Center Department of Biomedical Engineering Case Western Reserve University Cleveland OH USA

Stochastic resonance (SR) has been shown to enhance the signal to noise ratio or detection of signals in neurons. It is not yet clear how this effect of SR on the signal to noise ratio affects signal processing in neural networks. In this paper, we investigate the effects of the location of background noise input on information transmission in a hippocampai CA1 neuron model. In the computer simulation, random sub-threshold spike trains (signal) generated by a filtered homogeneous Poisson process were presented repeatedly to the middle point of the main apical branch, while the homogeneous Poisson shot noise (background noise) was applied to a location of the dendrite in the hippocampai CA1 model consisting of the soma with a sodium, a calcium, and five potassium channels. The location of the background noise input was varied along the dendrites to investigate the effects of background noise input location on information transmission. The computer simulation results show that the information rate reached a maximum value for an optimal amplitude of the background noise amplitude. It is also shown that this optimal amplitude of the background noise is independent of the distance between the soma and the noise input location. The results also show that the location of the background noise input does not significantly affect the maximum values of the information rates generated by stochastic resonance.

关键词： Action Potential Stochastic Resonance Hodgkin-Huxley model Homogeneous Poisson Process Shot Noise Synaptic Noise Information Rate Numerical Method Monte Carlo Simulation

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