2016 International Conference on Systems in Medicine and Biology (ICSMB)最新文献_第4页

A Fuzzy Graph Based Cluster Affinity Search Technique for clustering of gene expression data 基于模糊图的聚类亲和性搜索技术在基因表达数据聚类中的应用

2016 International Conference on Systems in Medicine and Biology (ICSMB) Pub Date : 1900-01-01 DOI: 10.1109/ICSMB.2016.7915092

Koyel Mandal, R. Sarmah, B. Borah

引用次数: 1

Content based retrieval of interstitial lung disease patterns using spatial distribution of intensity, gradient magnitude and gradient direction 基于内容的间质性肺疾病模式检索:基于强度、梯度大小和梯度方向的空间分布

2016 International Conference on Systems in Medicine and Biology (ICSMB) Pub Date : 1900-01-01 DOI: 10.1109/ICSMB.2016.7915087

Rahul Das Gupta, J. Dash, S. Mukhopadhyay

{"title":"Content based retrieval of interstitial lung disease patterns using spatial distribution of intensity, gradient magnitude and gradient direction","authors":"Rahul Das Gupta, J. Dash, S. Mukhopadhyay","doi":"10.1109/ICSMB.2016.7915087","DOIUrl":"https://doi.org/10.1109/ICSMB.2016.7915087","url":null,"abstract":"Today the enormous growth of medical images and scarcity of experienced pulmonologists and radiologists has led to the necessity of an efficient content-based image retrieval system capable of retrieve lung images similar to a given query image. This paper presents a promising texture-based image retrieval technique for interstitial lung disease categorisation by analysing the spatial distribution of intensity, along with its gradient magnitude and direction. The strengths of textural features derived from all different combinations of intensity, gradient magnitude and gradient direction are analysed. It is observed that both the magnitude and direction of intensity gradient contains significant textural information. Texture features can be substantially enriched by combining the features extracted from intensity, magnitude and direction of the intensity gradient as compared to that obtained from intensity alone. This approach is invariant to orientation of the texture and shape of the region of interest (ROI). The technique is simple, and is applicable to several other pattern recognition problems.","PeriodicalId":231556,"journal":{"name":"2016 International Conference on Systems in Medicine and Biology (ICSMB)","volume":"99 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117223858","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: 3

Image-based fuzzy c-means clustering and connected component labeling subsecond fast fully automatic complete cardiac cycle left ventricle segmentation in multi frame cardiac MRI images 基于图像模糊c均值聚类和连通分量标记的多帧心脏MRI图像亚秒快速全自动完整心周期左心室分割

2016 International Conference on Systems in Medicine and Biology (ICSMB) Pub Date : 1900-01-01 DOI: 10.1109/ICSMB.2016.7915082

Vinayak Ray, Ayush Goyal

{"title":"Image-based fuzzy c-means clustering and connected component labeling subsecond fast fully automatic complete cardiac cycle left ventricle segmentation in multi frame cardiac MRI images","authors":"Vinayak Ray, Ayush Goyal","doi":"10.1109/ICSMB.2016.7915082","DOIUrl":"https://doi.org/10.1109/ICSMB.2016.7915082","url":null,"abstract":"A rapid method for left ventricle extraction from MRI images of cardiac patients is presented in this research. This facilitates cardiologists to critically assess the cardiac function or dysfunction in a patient in terms of their left ventricle's performance, measured as its ejection fraction. Fuzzy c-means based pixel clustering is used for automatic segmentation. The left ventricle in all frames in the complete cardiac heartbeat cycle are extracted after being automatically loaded and segmented. In each image, pixels are grouped into two clusters - foreground and background. After the clustering, connected component analysis labels the pixels into connected regions. The left ventricle region is heuristically selected based on the distance from the image center and eccentricity. This novel original pixel clustering with labeling approach avoids manual initialization or user intervention. This method fully automatically extracts the left ventricle with more accuracy than manual tracing on all slices in the MRI images of the complete cardiac heartbeat cycle. The average computational processing speed per frame is 0.6 seconds, making it much more efficient than level sets, active contours, or other deformable methods, which need many iterations for the evolution of the snake or contour. Accuracy of the automated method presented herein was validated against manual tracing-based extraction. After performing the comparison on four MRI frames, it was found that an average correlation coefficient of 0.95 between the automatic and manual left ventricle segmented boundaries was higher than an average correlation coefficient of 0.85 between two manual tracing-based segmentations of the same.","PeriodicalId":231556,"journal":{"name":"2016 International Conference on Systems in Medicine and Biology (ICSMB)","volume":"39 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132524598","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: 11

Efficacy of FES for restoring hand grasp in hemiplegia: Investigation using biosignals FES对偏瘫患者手抓功能恢复的生物信号研究

2016 International Conference on Systems in Medicine and Biology (ICSMB) Pub Date : 1900-01-01 DOI: 10.1109/ICSMB.2016.7915074

Sehndkar C V, M. M., Lenka P K, K. Ratnesh, B. A

{"title":"Efficacy of FES for restoring hand grasp in hemiplegia: Investigation using biosignals","authors":"Sehndkar C V, M. M., Lenka P K, K. Ratnesh, B. A","doi":"10.1109/ICSMB.2016.7915074","DOIUrl":"https://doi.org/10.1109/ICSMB.2016.7915074","url":null,"abstract":"Rational behind conducting this randomized trial was to examine the therapeutic effect of functional electrical stimulation (FES) in stroke survivors having hand grasp problem. For this we used novel approach of tracking the motor condition changes instead of traditional method of measuring functional assessment scores. In the study subjects less than 9 months of stroke history with hand grasp difficulty were allocated to FES group (FES stimulation and physiotherapy, n□=□10) and control group (only physiotherapy, n□=□10) and imparted respective therapy for 5 days in week for 12 weeks. Two bio-signals (grip force and surface electromyography - sEMG) were measured at baseline and after the 12-week therapy from the Flexor Capri Radialis (FCR) muscle of the affected limb. Analysis of grip force measure confirmed that the FES significantly improve grip force in FES group (3.7N±0.5, p=0.014) when compare to control group. Also, sEMG analysis of stimulated muscle showed significant increase in amplitude (14.3±2.3µV, p=0.031), mean power frequency (5.2Hz±0.7, p=0.022) and median power frequency (6.2Hz±0.76, p=0.020) in the FES group. The results revealed that FES therapy instigates increase activation of stimulated muscle and also improves muscle condition. So, we conclude that FES combined with physiotherapy is effective for hand grasp rehabilitation than conventional physiotherapy.","PeriodicalId":231556,"journal":{"name":"2016 International Conference on Systems in Medicine and Biology (ICSMB)","volume":"211 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131619023","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

Study on life cycle of a sporogenous probiotic bacterium in mammalian gastrointestinal tract with image processing analysis 基于图像处理分析的哺乳动物胃肠道产孢益生菌生命周期研究

2016 International Conference on Systems in Medicine and Biology (ICSMB) Pub Date : 1900-01-01 DOI: 10.1109/ICSMB.2016.7915084

Subhasish Das, R. Sen, S. Bhattacharyya

引用次数: 0

Brain networks using nonlinear interdependence-based EEG synchronization: A study of human fatigue 基于非线性相互依赖的脑电同步的脑网络:人类疲劳的研究

2016 International Conference on Systems in Medicine and Biology (ICSMB) Pub Date : 1900-01-01 DOI: 10.1109/ICSMB.2016.7915114

A. Sengupta, A. Routray, Subhadeep Datta

引用次数: 2

Determining ocular gaze point fixation captured during triggered full saccades using EOG 利用EOG测定触发全扫视时捕获的眼球注视点注视

2016 International Conference on Systems in Medicine and Biology (ICSMB) Pub Date : 1900-01-01 DOI: 10.1109/ICSMB.2016.7915083

Suvodip Chakraborty, Aritra Chaudhuri, A. Dasgupta, A. Routray

引用次数: 2

MFCC feature with optimized frequency range: An essential step for emotion recognition 优化频率范围的MFCC功能:情感识别的重要步骤

2016 International Conference on Systems in Medicine and Biology (ICSMB) Pub Date : 1900-01-01 DOI: 10.1109/ICSMB.2016.7915112

Subhasmita Sahoo, A. Routray

{"title":"MFCC feature with optimized frequency range: An essential step for emotion recognition","authors":"Subhasmita Sahoo, A. Routray","doi":"10.1109/ICSMB.2016.7915112","DOIUrl":"https://doi.org/10.1109/ICSMB.2016.7915112","url":null,"abstract":"One of the major challenge in human emotion recognition is extraction of features containing maximum prosodic information. The accuracy of entire emotion detection system eventually relies upon the efficiency of the selected feature. When it comes to identifying emotions from voice, ambiguity in detection can never be completely avoided due to several reasons. Exclusion of redundant information to reduce confusion in recognizing emotions is quite challenging. The primary objective of this work is to improve the accuracy of existing emotion recognition method that uses Mel frequency Cepstral Coefficient (MFCC) feature. In this work, an additional step has been introduced to the method to make it more efficient for recognizing emotions from voice. Instead of taking the whole signal frequency range for filter bank analysis in MFCC computation, it has been suggested to optimize the analysis frequency range for maximum accuracy. The proposed method has been tested on two standard speech emotion databases: Berlin Emo-DB database [1] and Assamese database [2]. The addition of this extra step has been found to be increasing speaker-independent emotion recognition accuracy by 15% for Assamese database and around 25% for Berlin database.","PeriodicalId":231556,"journal":{"name":"2016 International Conference on Systems in Medicine and Biology (ICSMB)","volume":"172 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"131973488","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: 7

Combining respiratory regulation with breathing mechanism: Application to Cheyne-Stokes Respiration 呼吸调节与呼吸机制相结合:在Cheyne-Stokes呼吸中的应用

2016 International Conference on Systems in Medicine and Biology (ICSMB) Pub Date : 1900-01-01 DOI: 10.1109/ICSMB.2016.7915075

Tanmay Pal, S. Maka

{"title":"Combining respiratory regulation with breathing mechanism: Application to Cheyne-Stokes Respiration","authors":"Tanmay Pal, S. Maka","doi":"10.1109/ICSMB.2016.7915075","DOIUrl":"https://doi.org/10.1109/ICSMB.2016.7915075","url":null,"abstract":"Mathematical modeling approaches for the respiratory system are done on different abstraction=subsystem levels, depending upon the hypothesis and assumptions. Differential equations are used to describe dynamics of such systems. In the literature, various types of models are available. For example, some models describe the regulation of gases, on the other hand, some models link mouth pressure and air flow. Each of these models are complete for that particular subsystem, considering other subsystems of the body are at steady state. However, there are certain deviations, when a problem related to one subsystem is manifested in other subsystems. Cheyne-Stokes Respiration is one of such condition, which might generate from congestive heart failure or obstructive sleep apnea or central sleep apnea and it is reflected in waxing and waning of the tidal volume, possibly with the presence of apnea and hypopnea. These types of breathing patterns are caused by malfunction of the regulation system or cardiovascular system or neural system. In this work, combining models of the regulation system, breathing mechanism and neural system are considered. Using modulation hypothesis, the combined model is capable of generating Cheyne-Stokes Respiration waveforms. A new parameter, similar to modulation index is introduced to achieve different levels of apnea and hypopnea, which can quantify the diseased condition.","PeriodicalId":231556,"journal":{"name":"2016 International Conference on Systems in Medicine and Biology (ICSMB)","volume":"2017 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133504999","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

Retinal vessel segmentation under pathological conditions using supervised machine learning 在病理条件下使用监督机器学习进行视网膜血管分割

2016 International Conference on Systems in Medicine and Biology (ICSMB) Pub Date : 1900-01-01 DOI: 10.1109/ICSMB.2016.7915088

P. Rani, P. N., Rajkumar E. R., K. Rajamani

引用次数: 13