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and T1assessment of abdominal tissue response to graded hypoxia and hypercapnia using a controlled gas mixing circuit for small animals

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Journal of Magnetic Resonance Imaging 2016年第2期44卷

作者： Tameshwar Ganesh BSc Marvin Estrada BSc James Duffin PhD Hai Ling Cheng PhD Translational Biology & Engineering Program Ted Rogers Centre for Heart Research Toronto Canada Leslie Dan Faculty of Pharmacy University of Toronto Canada Physiology & Experimental Medicine Hospital for Sick Children Research Institute Toronto Canada Lab Animal Services Hospital for Sick Children Toronto Canada Department of Anesthesia University of Toronto Canada The Edward S. Rogers Sr. Department of Electrical & Computer Engineering University of Toronto Canada Institute of Biomaterials & Biomedical Engineering University of Toronto Canada

Purpose To characterize and T 1 relaxation time response to a wide spectrum of gas challenges in extracranial tissues of healthy rats. Materials and Methods A range of graded gas mixtures (hyperoxia, hypercapnia, hypoxia, and hypercapnic hypoxia) were delivered through a controlled gas-mixing circuit to mechanically ventilated and intubated rats. Quantitative magnetic resonance imaging (MRI) was performed on a 3T clinical scanner; and T 1 maps were computed to determine tissue response in the liver, kidney cortex, and paraspinal muscles. Heart rate and blood oxygen saturation (SaO 2 ) were measured through a rodent oximeter and physiological monitor. Results decreases consistent with lowered SaO 2 measurements were observed for hypercapnia and hypoxia, but decreases were significant only in liver and kidney cortex ( P < 0.05) for >10% CO 2 and <15% O 2 , with the new gas stimulus, hypercapnic hypoxia, producing the greatest decrease. Hyperoxia-related increases were accompanied by negligible increases in SaO 2 . T 1 generally increased, if at all, in the liver and decreased in the kidney. Significance was observed ( P < 0.05) only in kidney for >90% O 2 and >5% CO 2 . Conclusion and T 1 provide complementary roles for evaluating extracranial tissue response to a broad range of gas challenges. Based on both measured and known physiological responses, our results are consistent with as a sensitive marker of blood oxygen saturation and T 1 as a weak marker of blood volume changes. J. Magn. Reson. Imaging 2016;44:305–316.

关键词： gas challenge blood oxygen level dependent tissue oxygenation blood volume vasoreactivity

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Deep learning of image features from unlabeled data for multiple sclerosis lesion segmentation

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2014年 8679卷 117-124页

作者： Yoo, Youngjin Brosch, Tom Traboulsee, Anthony Li, David K.B. Tam, Roger Department of Electrical and Computer Engineering University of British Columbia VancouverBC Canada Biomedical Engineering Program University of British Columbia VancouverBC Canada Division of Neurology University of British Columbia VancouverBC Canada Department of Radiology University of British Columbia VancouverBC Canada

A new automatic method for multiple sclerosis (MS) lesion segmentation in multi-channel 3D MR images is presented. The main novelty of the method is that it learns the spatial image features needed for training a supervised classifier entirely from unlabeled data. This is in contrast to other current supervised methods, which typically require the user to preselect or design the features to be used. Our method can learn an extensive set of image features with minimal user effort and bias. In addition, by separating the feature learning from the classifier training that uses labeled (pre-segmented data), the feature learning can take advantage of the typically much more available unlabeled data. Our method uses deep learning for feature learning and a random forest for supervised classification, but potentially any supervised classifier can be used. Quantitative validation is carried out using 1450 T2-weighted and PD-weighted pairs of MRIs of MS patients, with 1400 pairs used for feature learning (100 of those for labeled training), and 50 for testing. The results demonstrate that the learned features are highly competitive with hand-crafted features in terms of segmentation accuracy, and that segmentation performance increases with the amount of unlabeled data used, even when the number of labeled images is fixed. © Springer International Publishing Switzerland 2014.

关键词： Magnetic resonance imaging

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A new approach to solve the inverse scattering problem using a differential evolution algorithm in distributed fiber bragg grating strain sensors

A new approach to solve the inverse scattering problem using...

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Latin America Optics and Photonics Conference, LAOP 2014

作者： Negri, L.H. Muller, M. Paterno, A.S. Fabris, J.L. Graduate Program in Electrical and Computer Engineering Federal University of Technology Paraná Curitiba80230-901 Brazil Department of Electrical Engineering Santa Catarina State University Joinville89219-710 Brazil

A differential evolution method is proposed to recover the deformation field in a fiber Bragg grating, overcoming known limitations of ambiguity and performance. Results show its capacity to determine deformation fiel... 详细信息

ISBN: (纸本)9781557528254

关键词： Fiber Bragg gratings

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Modulated High Frequency Oscillations Can Identify Regions of Interest in Human iEEG Using Hidden Markov Models

Modulated High Frequency Oscillations Can Identify Regions o...

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International IEEE/EMBS Conference on Neural engineering

作者： Mirna Guirgis Yotin Chinvarun Martin del Campo Peter L. Carlen Berj L. Bardakjian Institute of Biomaterials and Biomedical Engineering (IBBME) University of Toronto Toronto Canada Comprehensive Epilepsy Program and Neurology Unit Phramongkutklao Hospital Bangkok Thailand Division of Neurology University Health Network Toronto Canada Dept. of Physiol. University Health Network Toronto Canada Department of Electrical and Computer Engineering University of Toronto Toronto Canada

This study investigated the seizure and non-seizure state transitions in the intracranial electroencephalogram (iEEG) recordings of extratemporal lobe epilepsy patients. Cross-frequency coupling between low and high frequency oscillations in conjunction with an unsupervised learning algorithm - namely, hidden Markov models - was used to objectively identify seizure and non-seizure states as well as transition states. Channels consistently capturing two and/or three distinct states in a 32-channel iEEG array were able to identify regions of interest located in resected tissue of patients who experienced improved post-surgical outcomes.

关键词： Hidden Markov models Frequency modulation Training Oscillators Computational modeling Electrodes

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Fat percentage equation for children with cerebral palsy: A novel approach

Fat percentage equation for children with cerebral palsy: A ...

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13th Mediterranean Conference on Medical and Biological engineering and Computing 2013, MEDICON 2013

作者： Neves, E.B. Krueger, E. Rosário, B.R. Oliveira, M.C.N. Pol, S. Ripka, W.L. Campos de Andrade University Center Vitória Research Center Curitiba Brazil Federal Technological University of Paraná Graduate Program in Electrical Engineering and Computer Science Curitiba Brazil Federal Technological University of Paraná Graduate Program in Biomedical Engineering Curitiba Brazil

ISBN: (纸本)9783319008455

Nutritional changes are commonly related to children with cerebral palsy (CP), since these are problems as: dysphagia, vomiting and gastrointestinal reflux. For nutritional monitoring, body composition has become an important tool and has been present in this population assessments routine. In this sense, the aim of this study was to develop an equation for body composition estimate for children with cerebral palsy, aged between 5 and 6 years, using skinfolds, from the results of body composition obtained by Dual Energy X-rays Absormetry (DEXA). The study included 10 male children with cerebral palsy, aged between five and six-years-old, who participated in the physical therapy intensive program in Vitória research center, Curitiba, Brazil. Participants were assessed by: the Gross Motor Function Classification System;DEXA;and skinfold thickness. The skinfolds that showed better correlation with the total fat percentage and segmental fat percentage were: biceps and abdominal. The results of the regression analysis obtained equations to estimate the fat percentage by skinfold thickness with R2: 1.000 and 0.971, to seven and two skinfold thickness, respectively. In this sense, it is recommended to use the equation that utilizes the biceps and abdominal skinfolds thickness to estimate fat percentage of children with cerebral palsy, as this presents good estimation indicators. © Springer International Publishing Swit zerland 2014.

关键词： Biochemistry

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Identification of Brain Regions of Interest for Epilepsy Surgery Planning Using Support Vector Machines

Identification of Brain Regions of Interest for Epilepsy Sur...

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Annual International Conference of the IEEE engineering in Medicine and Biology Society

作者： Joshua A. Dian Sinisa Colic Yotin Chinvarun Peter L. Carlen Berj L. Bardakjian Department of Electrical and Computer Engineering University of Toronto Toronto M5S 3G4 Canada Comprehensive Epilepsy Program and Neurology Unit Pramongkutk-lao Hospital Bangkok 10400 Thailand Institute of Biomaterial and Biomedical Engineering University of Toronto Toronto M5S 3G9 Canada

ISBN: (纸本)9781424492695

In patients with intractable epilepsy, surgical resection is a promising treatment;however, post surgical seizure freedom is contingent upon accurate identification of the seizure onset zone (SOZ). Identification of the SOZ in extratemporal epilepsy requires invasive intracranial EEG (iEEG) recordings as well as resource intensive and subjective analysis by epileptologists. Expert inspection yields inconsistent localization of the SOZ which leads to comparatively poor post surgical outcomes for patients. This study employs recordings from 6 patients undergoing resection surgery in order to develop an automated and scalable system for identifying regions of interest (ROIs). Leveraging machine learning techniques and features used for seizure detection, a classification system was trained and tested on patients with Engel class I to class IV outcomes, demonstrating superior performance in the class I patients. Further, classification using features based upon both high frequency and low frequency oscillations was best able to identify channels suited for resection. This study demonstrates a novel approach to ROI identification and provides a path for developing tools to improve outcomes in epilepsy surgery.

关键词： EEG SOZ iEEG

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Evaluation of a mobile augmented reality application for image guidance of neurosurgical interventions

Evaluation of a mobile augmented reality application for ima...

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21st Medicine Meets Virtual Reality Conference, NextMed/MMVR 2014

作者： Kramers, Matthew Armstrong, Ryan Bakhshmand, Saeed M. Fenster, Aaron De Ribaupierre, Sandrine Eagleson, Roy Biomedical Engineering Graduate Program University of Western Ontario Canada Department of Clinical Neurological Sciences University of Western Ontario Canada Department of Electrical and Computer Engineering University of Western Ontario Canada Robarts Research Institute University of Western Ontario Canada

ISBN: (纸本)9781614993742

Image guidance can provide surgeons with valuable contextual information during a medical intervention. Often, image guidance systems require considerable infrastructure, setup-time, and operator experience to be utilized. Certain procedures performed at bedside are susceptible to navigational errors that can lead to complications. We present an application for mobile devices that can provide image guidance using augmented reality to assist in performing neurosurgical tasks. A methodology is outlined that evaluates this mode of visualization from the standpoint of perceptual localization, depth estimation, and pointing performance, in scenarios derived from a neurosurgical targeting task. By measuring user variability and speed we can report objective metrics of performance for our augmented reality guidance system.© 2014 The authors and IOS Press. All rights reserved.

关键词： Augmented reality

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A Simple Technique to Analysis of Microwave Absorbers using Frequency Selective Surfaces

A Simple Technique to Analysis of Microwave Absorbers using ...

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SBMO/IEEE MTT-S International Microwave and Optoelectronics Conference

作者： Eliel Poggi dos Santos Antonio Luiz P. S. Campos Graduate Program in Electrical and Computer Engineering Federal University of Rio Grande do Norte Department of Engineering Communications Federal University of Rio Grande do Norte

ISBN: (纸本)9781467394932

This work aims to analyze the variation of some parameters in the design of microwave absorbers using FSS. The methodology consists of a combination of two techniques: the equivalent circuit method, which provides the transmission and reflection characteristics of the individual structures for a plane wave with normal incidence, and the scattering matrix technique, which provides the result of two FSS cascaded, a conductive FSS and a resistive FSS, getting absorption properties in the projected range. Simulated results are presented and comparison with results obtained with commercial software are made.

关键词： Simple Technique Analysis Microwave Absorbers Frequency Selective Surfaces

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Using Bipartite Graphs for 3D Cardiac Model Retrieval

Using Bipartite Graphs for 3D Cardiac Model Retrieval

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Annual IEEE Symposium on computer-Based Medical Systems

作者： Leila C.C. Bergamasco Hellyan Oliveira Helton Bíscaro Harry Wechsler Fátima L.S. Nunes Polytechnic School - Graduate Program in Electrical Engineering University of Sao Paulo São Paulo SP Brasil Laboratory of Health Informatics Applications University of Sao Paulo São Paulo SP Brasil Department of Computer Science George Mason University Fairfax VA USA

Three-dimensional models have been used to aid medical diagnoses, using images generated by modalities like Magnetic Resonance Imaging. They can provide a more complete vision of objects since their depth is taken into account. Content-based Image Retrieval (CBIR) has also been used to aid the diagnosis. One important step in Three-dimensional CBIR (Model Retrieva) systems is the comparison between two models by using a set of features extracted and stored in a database. In this paper we present a novel method to compare two models, using the Bipartite graphs technique, with the aim to improve the retrieval precision. This technique retrieves 3D medical models of the left ventricle in order to aid the diagnosis of Congestive Heart Failure. Results showed that the novel method improved the precision by 10% when compared to the Similarity Function of Euclidean and Manhattan distance. These results confirmed that bipartite graph techniques can be used to improve the accuracy of Model Retrieval systems.

关键词： Solid modeling Three-dimensional displays Computational modeling Medical diagnostic imaging Feature extraction Bipartite graph

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Metadata Correction: Importance-Performance Analysis of Personal Health Records in Taiwan: A Web-Based Survey

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Journal of medical Internet research 2017年第6期19卷 e209页

作者： Hsiao-Hsien Rau Yi-Syuan Wu Chi-Ming Chu Fu-Chung Wang Min-Huei Hsu Chi-Wen Chang Kang-Hua Chen Yen-Liang Lee Senyeong Kao Yu-Lung Chiu Hsyien-Chia Wen Anis Fuad Chien-Yeh Hsu Hung-Wen Chiu Graduate Institute of Biomedical Informatics Taipei Medical University Taipei Taiwan. Administration Department Healthconn Corp Taipei Taiwan. Institute of Medical Informatics Department of Computer Science of Information Engineering National Cheng Kung University Tainan Taiwan. School Of Public Health National Defense Medical Center Taiepi Taiwan. National Health Insurance Administration Ministry of Health and Welfare Taiepi Taiwan. School of Nursing College of Medicine Chang Gung University Linkou Taiwan. Division of Endocrinology Department of Pediatrics Linkou Chang Gung Memorial Hospital Linkou Taiwan. Internet of Things Laboratory Chunghwa Telecom Laboratories TaoYuen Taiwan. School of Health Care Administration Taipei Medical University Taipei Taiwan. Department of Biostatistics Epidemiology and Population Health Faculty of Medicine Universitas Gadjah Mada Yogyakarta Indonesia. Department of Information Management National Taipei University of Nursing and Health Sciences Taipei Taiwan. Master Program in Global Health and Development Taipei Medical University Taipei Taiwan.

[This corrects the article DOI: .].

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