Proceedings of the 2018 3rd International Conference on Biomedical Imaging, Signal Processing最新文献_第2页

Fast Estimation of Downsampling Factor for Biomedical Image Registration 生物医学图像配准中降采样因子的快速估计

Proceedings of the 2018 3rd International Conference on Biomedical Imaging, Signal Processing Pub Date : 2018-10-11 DOI: 10.1145/3288200.3288203

A. Krylov, F. Guryanov, N. Mamaev, D. Yurin

引用次数: 1

Development of an Electromagnetic Tracking System for Surgical Instruments Positioning 手术器械定位电磁跟踪系统的研制

Proceedings of the 2018 3rd International Conference on Biomedical Imaging, Signal Processing Pub Date : 2018-10-11 DOI: 10.1145/3288200.3288216

F. Attivissimo, A. Nisio, A. Lanzolla, S. Selicato, P. Larizza

引用次数: 0

Automatic Segmentation of HEp-2 Cells Based on Active Contours Model 基于活动轮廓模型的HEp-2细胞自动分割

Proceedings of the 2018 3rd International Conference on Biomedical Imaging, Signal Processing Pub Date : 2018-10-11 DOI: 10.1145/3288200.3288204

Donato Cascio, V. Taormina, G. Raso

{"title":"Automatic Segmentation of HEp-2 Cells Based on Active Contours Model","authors":"Donato Cascio, V. Taormina, G. Raso","doi":"10.1145/3288200.3288204","DOIUrl":"https://doi.org/10.1145/3288200.3288204","url":null,"abstract":"In the past years, a great deal of effort was put into research regarding Indirect Immunofluorescence techniques with the aim of development of CAD systems. In this work a method for segmenting HEp-2 cells in IIF images is presented. Such task is one of the most challenging of automated IIF analysis, because the segmentation algorithm has to cope with a large heterogeneity of shapes and textures. In order to address this problem, numerous techniques and their combinations were evaluated, in a process aimed at maximizing the figure of merit. The proposed method, for a greater definition of cellular contours, uses the active contours in the last phase of the process. The initial conditions, center position and initial curve of the active contour, were obtained using a randomized Hough transform for ellipse; the idea in identifying cells was to approximate them initially to ellipses. The purpose of the active contours, within the segmentation process, is to allow the separation of connected regions (such as two overlapping cells), in order to obtain a better definition of the objects to be analyzed (the cells). Our system has been developed and tested on public database. Segmentation performances were evaluated in terms of Dice index and the method was compared with other state-of-the-art workers. The results obtained demonstrate the goodness of the method in the characterization of HEp-2 cells. The developed method shows great strength and convergence speed. Furthermore, the flexibility of the proposed method allows it to be easily used in other biomedical contexts.","PeriodicalId":152443,"journal":{"name":"Proceedings of the 2018 3rd International Conference on Biomedical Imaging, Signal Processing","volume":"60 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128602075","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

Proceedings of the 2018 3rd International Conference on Biomedical Imaging, Signal Processing 2018第三届生物医学成像，信号处理国际会议论文集

Proceedings of the 2018 3rd International Conference on Biomedical Imaging, Signal Processing Pub Date : 2018-10-11 DOI: 10.1145/3288200

引用次数: 0

Machine Learning and DSP Algorithms for Screening of Possible Osteoporosis Using Electronic Stethoscopes 使用电子听诊器筛选骨质疏松症的机器学习和DSP算法

Proceedings of the 2018 3rd International Conference on Biomedical Imaging, Signal Processing Pub Date : 2018-10-11 DOI: 10.1145/3288200.3288215

Jamie Scanlan, Francis F. Li, O. Umnova, G. Rakoczy, Nóra Lövey

{"title":"Machine Learning and DSP Algorithms for Screening of Possible Osteoporosis Using Electronic Stethoscopes","authors":"Jamie Scanlan, Francis F. Li, O. Umnova, G. Rakoczy, Nóra Lövey","doi":"10.1145/3288200.3288215","DOIUrl":"https://doi.org/10.1145/3288200.3288215","url":null,"abstract":"Osteoporosis is a prevalent but asymptomatic condition that affects a large population of the elderly, resulting in a high risk of fracture. Several methods have been developed and are available in general hospitals to indirectly assess the bone quality in terms of mineral material level and porosity. In this paper we describe a new method that uses a medical reflex hammer to exert testing stimuli, an electronic stethoscope to acquire impulse responses from tibia, and intelligent signal processing based on artificial neural network machine learning to determine the likelihood of osteoporosis. The proposed method makes decisions from the key components found in the time-frequency domain of impulse responses. Using two common pieces of clinical apparatus, this method might be suitable for the large population screening tests for the early diagnosis of osteoporosis, thus avoiding secondary complications. Following some discussions of the mechanism and procedure, this paper details the techniques of impulse response acquisition using a stethoscope and the subsequent signal processing and statistical machine learning algorithms for decision making. Pilot testing results achieved over 80% in detection sensitivity.","PeriodicalId":152443,"journal":{"name":"Proceedings of the 2018 3rd International Conference on Biomedical Imaging, Signal Processing","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115715495","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

Long-Term Sleep Assessment by Unobtrusive Pressure Sensor Arrays 不显眼的压力传感器阵列长期睡眠评估

Proceedings of the 2018 3rd International Conference on Biomedical Imaging, Signal Processing Pub Date : 2018-10-11 DOI: 10.1145/3288200.3288214

S. S. Gilakjani, M. Bouchard, R. Goubran, F. Knoefel

{"title":"Long-Term Sleep Assessment by Unobtrusive Pressure Sensor Arrays","authors":"S. S. Gilakjani, M. Bouchard, R. Goubran, F. Knoefel","doi":"10.1145/3288200.3288214","DOIUrl":"https://doi.org/10.1145/3288200.3288214","url":null,"abstract":"Due to a globally aging population, there is a growing demand for smart home technology which can serve to monitor the health and safety of older adults. Sleep monitoring has emerged as a crucial element of this monitoring. While polysomnography (PSG) is an effective and accurate tool for sleep monitoring, it is obtrusive as the user must wear the instruments during the experiment. Therefore, there has been a growing interest in deploying unobtrusive sleep monitoring devices, specifically for long-term patient monitoring. This paper performs a comprehensive investigation on long-term sleep pattern changes by investigating bed occupancy, number of bed exits during day and breathing rate variability. Measurements were made using unobtrusive pressure sensitive sensor arrays on data captured from several participants collected in a long-term basis, which provided a large volume of data. Multiple algorithms are proposed that can be described as movement detection, sensor data fusion and bed occupancy detection. The methods developed in the paper and the related findings can be of interest for future clinical remote patient monitoring systems.","PeriodicalId":152443,"journal":{"name":"Proceedings of the 2018 3rd International Conference on Biomedical Imaging, Signal Processing","volume":"119 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116037690","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: 8

Three-Dimensional Reconstruction of Cardiac Structures Using CT Images 基于CT图像的心脏结构三维重建

Proceedings of the 2018 3rd International Conference on Biomedical Imaging, Signal Processing Pub Date : 2018-10-11 DOI: 10.1145/3288200.3288210

Luis Lopez Diaz, Andersson Contreras Olmos, A. Cadena, W. Percybrooks, Juan Pablo Tello P.

{"title":"Three-Dimensional Reconstruction of Cardiac Structures Using CT Images","authors":"Luis Lopez Diaz, Andersson Contreras Olmos, A. Cadena, W. Percybrooks, Juan Pablo Tello P.","doi":"10.1145/3288200.3288210","DOIUrl":"https://doi.org/10.1145/3288200.3288210","url":null,"abstract":"This paper describes a software tool for building and displaying tri-dimensional cardiac structures from a sequence of Computer Tomography (CT) scan images. The development process followed for this work can be divided into 5 stages. During the first stage, suitable DICOM images are selected from a CT scan machine. In the second stage, the images are pre-processed in order to reduce noise levels and enhance relevant features. The third stage compares the performance of three image segmentation methods on the pre-processed images: Region growing, Otsu's algorithm and active contours. It was found that active contours achieves the best isolation of the Region of Interest (ROI), while the other two methods recognized morphological structures outside of the ROI. In the four stage, a 3D image of the ROI is renderized. Finally, the reconstructed 3D model is visualized in stage five using a custombuilt Graphical User Interface (GUI). The resulting 3D models are validated by visual inspection by three heart and imaging experts, which determine if the model is suitable for use in diagnosis or surgery planning.","PeriodicalId":152443,"journal":{"name":"Proceedings of the 2018 3rd International Conference on Biomedical Imaging, Signal Processing","volume":"69 1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-10-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123247991","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: 1