2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA)最新文献_第7页

A synthetic instrument for diagnosis and performance measurement of Individuals with Visual Sequential Memory Deficit 一种用于视觉顺序记忆缺陷诊断和性能测量的综合仪器

2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Pub Date : 2017-05-01 DOI: 10.1109/MeMeA.2017.7985843

Ayşe Rumeysa Mohammed, Ammar Rashed, S. Shirmohammadi

引用次数: 2

Scintillation sensing of 18F-FDG for the detection of metabolically active atherosclerotic plaque 18F-FDG的闪烁感应检测代谢活性动脉粥样硬化斑块

2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Pub Date : 2017-05-01 DOI: 10.1109/MeMeA.2017.7985851

Michael Burke, K. Dennis, A. Lerman, G. Sandhu, F. Franchi, Mark A. Benscoter, M. Rodriguez-Porcel

{"title":"Scintillation sensing of 18F-FDG for the detection of metabolically active atherosclerotic plaque","authors":"Michael Burke, K. Dennis, A. Lerman, G. Sandhu, F. Franchi, Mark A. Benscoter, M. Rodriguez-Porcel","doi":"10.1109/MeMeA.2017.7985851","DOIUrl":"https://doi.org/10.1109/MeMeA.2017.7985851","url":null,"abstract":"Atherosclerosis and its consequences are the main cause of mortality in the United States and the western world. Detection of metabolically active regions of atherosclerotic plaque can provide insights on those plaques that are prone to rupture, leading to a tissue infarction. The metabolic activity of these plaques can be identified using positron emission tomography (PET). However, such detection has been elusive in the coronary arteries due to motion and detection sensitivity. One of the techniques capable of improving precision as an affordable alternative is the use of an optical scintillating fiber for the detection of 18-Fluorine Fluorodeoxyglucose (18F-FDG), a compound that is accumulated in metabolically active areas of the atherosclerotic plaque. Here we report on a prototype scintillating fiber detection system designed to characterize the beta emission, particularly positron emission, by 18F-FDG. We demonstrate the ability to effectively measure the presence of 18F-FDG contained in-vivo along with the ability discriminate against ambient light based on energy. This paper presents a catheter-based hardware and software platform based on the use of a scintillating fiber optic catheter. The system measures a short (2–3 ns) burst of photons that are generated by the stimulation of the plastic scintillating fiber by a positron (633 kEv) emitted by the radioactive compound. It can be used to determine the presence of 18F-FDG in-vivo and accurately detect the active decay as the 18F-FDG retained in the metabolically active plaque. The proposed instrument was tested in-vitro and its sensitivity was also measured in-vivo. The developed system may be used in the detection of 18F-FDG, as surrogate of inflammation, providing critical in-vivo information of the metabolism in areas of inflammation.","PeriodicalId":235051,"journal":{"name":"2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132857697","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

Sparse diploid spatial biosignal recovery for genomic variation detection 稀疏二倍体空间生物信号恢复用于基因组变异检测

2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Pub Date : 2017-05-01 DOI: 10.1109/MeMeA.2017.7985888

Mario Banuelos, Lasith Adhikari, R. Almanza, Andrew Fujikawa, Jonathan Sahagun, Katharine Sanderson, M. Spence, Suzanne S. Sindi, Roummel F. Marcia

{"title":"Sparse diploid spatial biosignal recovery for genomic variation detection","authors":"Mario Banuelos, Lasith Adhikari, R. Almanza, Andrew Fujikawa, Jonathan Sahagun, Katharine Sanderson, M. Spence, Suzanne S. Sindi, Roummel F. Marcia","doi":"10.1109/MeMeA.2017.7985888","DOIUrl":"https://doi.org/10.1109/MeMeA.2017.7985888","url":null,"abstract":"Structural variants (SVs) - such as duplications, deletions and inversions - are rearrangements of an individual's genome relative to a given reference. The common method for detection of SVs is to sequence fragments from an individual's genome, map them to the appropriate reference and, by identifying discordant mappings, predict the locations and type of SV. However, errors in both the sequencing and mapping process will result in signals that look like SVs, resulting in inaccurate predictions. In addition, because of variation in sequencing coverage even when the evidence of an SV is present, determining if an individual has the SV present on one or both of their chromosomes is challenging. In our work, we seek to improve upon standard methods for SV detection in three ways. First, to reduce false-positive predictions, we simultaneously predict SVs in a parent and child using properties of inheritance to constrain the space of possible SVs. Second, we predict if a variant is homozygous (SV is on two chromosomes) or heterozygous (SV is on one chromosome). Third, we utilize a gradient-based optimization approach and constrain our solution with a sparsity-promoting ℓ1 penalty (since SV instances should be rare). We demonstrate the improved performance of our computational approach on both simulated genomes as well as a parent-child trio from the 1000 Genomes Project.","PeriodicalId":235051,"journal":{"name":"2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"97 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133131431","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: 4

A real-time smartphone-based floor detection system for the visually impaired 为视障人士设计的实时智能手机地板探测系统

2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Pub Date : 2017-05-01 DOI: 10.1109/MeMeA.2017.7985844

Y. DeLaHoz, M. Labrador

{"title":"A real-time smartphone-based floor detection system for the visually impaired","authors":"Y. DeLaHoz, M. Labrador","doi":"10.1109/MeMeA.2017.7985844","DOIUrl":"https://doi.org/10.1109/MeMeA.2017.7985844","url":null,"abstract":"According to the American Foundation for the Blind (AFB) more than 25 million people in the U.S. suffer from total or partial vision loss. Assistive technologies have been a pivotal tool to enhance blind people's lives in the last 20 years. Fall prevention (FP) is a research area that has been active for over a decade to improve people's lives through the use of pervasive computing. This work introduces a smartphone-based fall prevention system for the blind and elaborates on the first module: a floor detection system for indoor environments using a smartphone's camera. Image-based floor detection encompasses multiple stages that makes the entire process remarkably difficult. This difficulty is increased due to the complexity of current algorithms, the limited amount of resources available in mobile devices, the movement of the camera while walking, and the real time nature of the system. This paper provides a general description of the fall prevention system along with its challenges and current solutions. Then, a detailed description of the floor detection system is provided including its five modules: smoothing, edge detection, line detection, wall-floor boundary detection, and floor detection. Finally, the floor detection module evaluation shows an accuracy of 82%, a precision of 90.3%, and a recall of 75%.","PeriodicalId":235051,"journal":{"name":"2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132646211","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: 6

Analysis of mylenated nerve fibers using an image acquisition system 用图像采集系统分析髓系神经纤维

2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Pub Date : 2017-05-01 DOI: 10.1109/MeMeA.2017.7985848

David M. Johnson, Mark B. Wehde, P. Dyck, JaNean K. Engelsted, J. Davies

{"title":"Analysis of mylenated nerve fibers using an image acquisition system","authors":"David M. Johnson, Mark B. Wehde, P. Dyck, JaNean K. Engelsted, J. Davies","doi":"10.1109/MeMeA.2017.7985848","DOIUrl":"https://doi.org/10.1109/MeMeA.2017.7985848","url":null,"abstract":"A system to evaluate and follow morphologic changes in number, size, shape and other histological measurements of transverse myelinated fiber profiles in nerves and fiber tracts has proven to be a useful analysis tool. Applications of the system include the enumeration and sizing of peripheral nerves and central nervous system tracts for the morphologic study of development, aging, regeneration, neurotoxicity, pathologic conditions, also, the morphometric assessment of intra-epidermal nerve fiber densities, IENFD. The primary aim of the system is to provide both an operator-interactive and automated method for the detection, sizing and measurement of myelinated fibers. The system, Imaging System for Nerve Morphometry, was shown, to provide the specific functionality required to perform morphometric studies of peripheral nerve, compared to commercial systems which perform a more general estimate of histological features. The system consists of the tissue preparation process, a video camera-ready microscope capable of various resolutions, and a computer system for image acquisition, data analysis, data display and statistical analysis. The morphometric measurements obtained from this system have been used for quality control by clinical nerve pathologists, in the study of human peripheral neuropathies and the clinical assessment of IENFDs. In assessment of test retest reproducibility of periodically-sampled nerves, high degrees of reproducibility were achieved for most morphometric measurements.","PeriodicalId":235051,"journal":{"name":"2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133082644","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

Novel method measures current distribution in muscle tissue under applied voltage 新方法测量施加电压下肌肉组织中的电流分布

2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Pub Date : 2017-05-01 DOI: 10.1109/MeMeA.2017.7985884

Steven E. Nowakowski

引用次数: 0

Gastrointestinal cancer diagnostics by terahertz time domain spectroscopy 太赫兹时域光谱诊断胃肠道癌症

2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Pub Date : 2017-05-01 DOI: 10.1109/MeMeA.2017.7985863

A. A. Goryachuk, A. A. Simonova, M. Khodzitsky, M. Borovkova, A. Khamid

引用次数: 16

Computer-aided classification of multi-types of dementia via convolutional neural networks 基于卷积神经网络的多类型痴呆的计算机辅助分类

2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Pub Date : 2017-05-01 DOI: 10.1109/MeMeA.2017.7985847

Elham M. Alkabawi, A. Hilal, O. Basir

{"title":"Computer-aided classification of multi-types of dementia via convolutional neural networks","authors":"Elham M. Alkabawi, A. Hilal, O. Basir","doi":"10.1109/MeMeA.2017.7985847","DOIUrl":"https://doi.org/10.1109/MeMeA.2017.7985847","url":null,"abstract":"With millions of people suffering from dementia worldwide, the global prevalence of dementia has a significant impact on the patients' lives, their caregivers' physical and emotional states, and the global economy. Early diagnosis of dementia helps in finding suitable therapies that reduce or even prevent further deterioration of patients' cognitive abilities. In recent years, state-of-the-art literature has proposed various computer-aided diagnosis systems based on 3-dimensional brain imagery analysis to identify early symptoms of dementia. These systems aim to assist radiologists in increasing the accuracy of diagnoses and reducing false positives. However, the early diagnosis of dementia is a challenging task due to the image quality, noise, and human brain irregularities. The state-of-the-art has focused on differentiating multi-stages of Alzheimer's disease, however, the diagnosis of various types of dementia is still a gap. This paper proposes a deep learning-based computer-aided diagnosis approach for the early detection of multi-type of dementia. To show the performance of the proposed CAD algorithm, three conventional CAD methods are implemented for comparison. The proposed algorithm yields a 74.93% accuracy in early diagnosis of multi-type of dementia and outperforms the state of the art CAD methods.","PeriodicalId":235051,"journal":{"name":"2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"123 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123356101","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: 10

Feasibility of detecting ADHD patients' attention levels by classifying their EEG signals 通过脑电信号分类检测ADHD患者注意水平的可行性

2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Pub Date : 2017-05-01 DOI: 10.1109/MeMeA.2017.7985895

Alaa Eddin Alchalabi, M. Elsharnouby, S. Shirmohammadi, Amer Nour Eddin

{"title":"Feasibility of detecting ADHD patients' attention levels by classifying their EEG signals","authors":"Alaa Eddin Alchalabi, M. Elsharnouby, S. Shirmohammadi, Amer Nour Eddin","doi":"10.1109/MeMeA.2017.7985895","DOIUrl":"https://doi.org/10.1109/MeMeA.2017.7985895","url":null,"abstract":"Attention Deficit Hyperactivity Disorder (ADHD), characterized by the lack of attention and focus, is one of the most spread cognitive disorders. Since electroencephalogram (EEG) signals carry extensive information about cognition skills, which include attention, then the potential of using EEG signals for people with low attention span can be quite significant. EEG can be read using the new wireless EEG reading devices often used by Brain-computer Interface (BCI) researchers. In parallel, serious games have been recently utilized for rehabilitating various cognitive and emotional deficits. In this paper, we put the two things together, and we investigate the integration of an EEG-controlled serious game that trains and strengthens patients' attention ability while using machine learning to detect their attention level. Our preliminary experiments with healthy individuals show an accuracy of up to 96% in classifying the EEG data to detect the correct attention state during gameplay. This promising result serves as motivation to test our models with actual ADHD patients in the future.","PeriodicalId":235051,"journal":{"name":"2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2017-05-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121558146","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: 14

Wave propagation with HBC in a human arm model HBC在人体手臂模型中的波传播

2017 IEEE International Symposium on Medical Measurements and Applications (MeMeA) Pub Date : 2017-05-01 DOI: 10.1109/MeMeA.2017.7985918

Doaa Ahmed, J. Kirchner, G. Fischer

引用次数: 2