2018 Fourth International Conference on Biosignals, Images and Instrumentation (ICBSII)最新文献

{"title":"Event Schedule","authors":"G. Gill","doi":"10.1109/mpe.2018.2811286","DOIUrl":"https://doi.org/10.1109/mpe.2018.2811286","url":null,"abstract":"Distinguished University Professor and Dean.","PeriodicalId":262474,"journal":{"name":"2018 Fourth International Conference on Biosignals, Images and Instrumentation (ICBSII)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2023-07-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"121091156","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}

{"title":"Cover Page","authors":"Christoph E. Koch, M. Garofalakis, D. Srivastava, K. Aberer, W. Klas, E. Neuhold","doi":"10.1093/jat/bkw076","DOIUrl":"https://doi.org/10.1093/jat/bkw076","url":null,"abstract":"Department of Biomedical Engineering Centre for Healthcare Technologies.","PeriodicalId":262474,"journal":{"name":"2018 Fourth International Conference on Biosignals, Images and Instrumentation (ICBSII)","volume":"115 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132834191","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}

{"title":"Computer Aided System for Human Blood Cell Identification, Classification and Counting","authors":"N. Christy Evangeline, M. Annalatha","doi":"10.1109/ICBSII.2018.8524636","DOIUrl":"https://doi.org/10.1109/ICBSII.2018.8524636","url":null,"abstract":"Evaluation of Blood Smear is one of the most basic laboratory procedures in Hematology as deviations of blood cell count from their reference values can be indicators of various disease conditions. Digital Image Processing can help the technologists in the analysis and classification of blood cells and diagnosis of certain health conditions based on the CBC values and their morphology. This project aims at generating software that can identify, classify and count various blood cells from the peripheral blood smear samples. Locating, identifying and counting of Blood cells manually can be tedious, time consuming and inaccurate. On the other hand, Automatic Hematology Analyzers that work on Flow cytometry principle for classification are expensive and can perform only quantitative analysis. Thus taking into consideration, the wide scope of Image processing in the field of medicine, this proposed work aims to generate a preliminary framework of Automatic Analysis of Human Blood smear for identification, classification and counting of blood cells by using various Image processing.","PeriodicalId":262474,"journal":{"name":"2018 Fourth International Conference on Biosignals, Images and Instrumentation (ICBSII)","volume":"27 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123545575","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}

{"title":"Robustness of Single Ended Measurement to Electrode Errors in Electrical Impedance Tomography: An Experimental Study","authors":"M. Verma, D. Gharpure, V. Wagh","doi":"10.1109/ICBSII.2018.8524639","DOIUrl":"https://doi.org/10.1109/ICBSII.2018.8524639","url":null,"abstract":"Detachment of electrodes is the most common problem in EIT while monitoring due to patient's movement or sweat etc. which results in significant image artifacts. Though several compensation strategies had been proposed to manage these errors, however it also degrades the quality of actual image especially if the target is closer to the electrodes. The degradation effect not only depends on the compensation strategy but also on the measurement methodology used. It has already been reported earlier that for the adjacent method (differential measurement) the actual images are not significantly affected if the target is at a distance greater than 15% of the diameter from the affected electrode. Recently single ended measurements with internal electrode have gained more popularity because of its greater sensitivity. This paper reports on the robustness of single ended measurement towards electrode errors. In vitro studies are carried out for single ended measurement(common ground method) and differential measurement(adjacent method) to find how the actual images are affected after compensating for electrode errors as the target moves closer to the affected electrode and as the number of failed electrodes increases. Adjacent electrodes are removed to have the maximum effect on the target as the target is placed closer to the affected electrodes. Different algorithms had been suggested earlier to detect these faulty electrodes in case of differential measurements. In this paper we have also discussed the applicability of current voltage reciprocity principle to automatically detect faulty electrodes in case of single ended measurement. Maximum number of adjacent and non-adjacent faulty electrodes that can be detected for both methods using the algorithm is reported. It is observed that for single ended measurement up to four adjacent faulty electrodes are detected however, in case of adjacent method only up to two faulty electrodes are detected. Bayesian imaging model, where electrode errors are fed as a priori large measurement noise on all measurements using affected electrode is used to account for the erroneous data. In case of single ended measurement there isn't any significant change in resolution and position error of the reconstructed image for 1 faulty electrode if the target is at a distance greater than or equal to 10% of the diameter from the electrodes. Also for single ended measurement the images are not significantly affected even for 3 adjacent faulty electrodes after compensation. Overall, results indicate that single ended measurement is more robust and gives better images than differential measurement after compensating for electrode errors.","PeriodicalId":262474,"journal":{"name":"2018 Fourth International Conference on Biosignals, Images and Instrumentation (ICBSII)","volume":"89 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134506650","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}

{"title":"Epileptic Seizure Prediction Based on Localization","authors":"S. Hussain","doi":"10.1109/ICBSII.2018.8524811","DOIUrl":"https://doi.org/10.1109/ICBSII.2018.8524811","url":null,"abstract":"Electroencephalography (EEG) gives complex information about the brain dynamics. Visual Inspection of EEG signal is difficult and requires skilled interpreters in identifying epileptic seizures. One third of the people having epilepsy are drug resistant and the latest anti-epileptic drugs cannot stop the seizures completely. Unexpected occurrence of seizure disturbs the quality of life and causes physical damage. The Prediction based on localization of Epileptic Zone using EMD and neural network has resulted excellent prediction accuracy. A seizure prediction time of 30.4 minutes was achieved. It can be used as a clinical application for the diagnosis and effective epilepsy management.","PeriodicalId":262474,"journal":{"name":"2018 Fourth International Conference on Biosignals, Images and Instrumentation (ICBSII)","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132361959","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}

{"title":"Myoelectric Control System Based on Wavelet Features","authors":"Supriya Mary Sunil, K. I. Ramachandran","doi":"10.1109/ICBSII.2018.8524838","DOIUrl":"https://doi.org/10.1109/ICBSII.2018.8524838","url":null,"abstract":"Electromyography (EMG) finds enormous applications in clinical/biomedical, prosthesis and rehabilitation devices. The main objective of this paper is to develop a cost-effective implementation of a prosthetic control system based on EMG signals. Non-invasive surface electrodes are used to acquire the signal for various actions. Since the signal is highly contaminated with noise, they are not used in its raw form to handle any sort of device. Amplification and filtering are therefore inevitable and becomes the foremost task prior to further processing so as to obtain a high-quality signal. After the conditioning of the signal, multi-level decomposition based on wavelet transform is performed and features are extracted from all the levels. They are then reduced to find the optimal performance. Finally, the selected features are able to distinguish between various hand movements and therefore helps in the recognition of the intended motion of the amputee.","PeriodicalId":262474,"journal":{"name":"2018 Fourth International Conference on Biosignals, Images and Instrumentation (ICBSII)","volume":"55 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"133377434","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}

{"title":"An Approach to Extract Optic-Disc from Retinal Image Using K-Means Clustering","authors":"N. Kowsalya, A. Kalyani, C. J. Chalcedony, R. Sivakumar, M. Janani, V. Rajinikanth","doi":"10.1109/ICBSII.2018.8524655","DOIUrl":"https://doi.org/10.1109/ICBSII.2018.8524655","url":null,"abstract":"Generally, retinal picture valuation is commonly executed to appraise the diseases. In this paper, an image examination technique is implemented to extract the Retinal-Optic-Disc (ROD) to assess its condition. An approach based on the combination of Kapur's entropy and K-means clustering is considered here to mine the optic disc region from the RGB retinal picture. During the experimental implementation, this approach is tested with the DRIVE and RIM-ONE databases. Initially, the DRIVE pictures are considered to appraise the proposed approach and later, the RIM-ONE dataset is considered for the testing. After extracting the ROD, comparative analyses with the expert's Ground-Truths are carried out and the image similarity values are then recorded. This approach is then validated against the Otsu's+levelset existing in the literature. All these experiments are implemented using Matlab2010. The outcome of this procedure confirms that, proposed work provides better picture similarity values compared to Otsu's+levelset. Hence, in future, this procedure can be considered to evaluate the clinical retinal images.","PeriodicalId":262474,"journal":{"name":"2018 Fourth International Conference on Biosignals, Images and Instrumentation (ICBSII)","volume":"116 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124004439","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}

{"title":"Colour Image Segmentation of Fundus Blood Vessels for the Detection of Hypertensive Retinopathy","authors":"M. Anna Latha, N. Christy Evangeline, S. Sankaranarayanan","doi":"10.1109/ICBSII.2018.8524781","DOIUrl":"https://doi.org/10.1109/ICBSII.2018.8524781","url":null,"abstract":"Retina is the major part of the human eye. Most of the diabetic and hypertensive problems will initially affect the retinal blood vessels of the eye. Using normal segmentation techniques, we can identify only the blood vessels. Therefore, color image segmentation is the best way to identify the retinal problems, because using color image segmentation we can differentiate the retinal veins and arteries. We have used masking techniques to segment the images of arteries and vein. The proposed technique is evaluated with data from ten patients diagnosed with hypertensive retinopathy. For this process, histogram equalization is performed on the complemented green plane image. From the result, the optic region is removed by morphological operation, after which it is converted into binary image. This output is multiplied with R, G, & B channels of input data and combined to get required segmented region of retinal blood vessels. All this vessels extraction has been done by using image processing techniques.","PeriodicalId":262474,"journal":{"name":"2018 Fourth International Conference on Biosignals, Images and Instrumentation (ICBSII)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115879443","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}

{"title":"Comparison of Envelope Detection and Signal Normalization Methods for Foetal Heart Rate Extraction from Foetal Heart Sound","authors":"B. Amrutha, M. Arora","doi":"10.1109/ICBSII.2018.8524718","DOIUrl":"https://doi.org/10.1109/ICBSII.2018.8524718","url":null,"abstract":"Foetal heart rate is an important indicator of foetal well-being which indicates fetal distress during antepartum and intrapartum period. This paper provides systematic comparison of four different methods envelope detection and four different methods of signal normalization to determine the fetal heart rate from fetal heart sound. To obtain the ground truth, each heart beat was manually identified by visualizing the sound recording on a computer screen. Four different measure of error are used compare various combinations of envelop detection and normalization methods. It is found that the homomorphic filtering gave highest accuracy. Choice of normalization methods did not affect accuracy measurement in most cases.","PeriodicalId":262474,"journal":{"name":"2018 Fourth International Conference on Biosignals, Images and Instrumentation (ICBSII)","volume":"117 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124173024","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}

{"title":"Raman Monte Carlo Simulation of Tooth Model with Embedded Sphere for Different Launch Beam Configurations","authors":"Subitcha Jayasankar, Vijitha Periyasamy, S. Umapathy, M. Pramanik","doi":"10.1109/ICBSII.2018.8524632","DOIUrl":"https://doi.org/10.1109/ICBSII.2018.8524632","url":null,"abstract":"The Monte Carlo simulation of light transport in multi-layered tissue is utilized to implement Raman scattering. The unique molecular signature of Raman spectroscopy makes it a highly potential technique for many medical applications including structural analysis of tooth. To provide an environment for the developmental defect of dentine such as dentinogenesis imperfecta, an embedded sphere is introduced in the simulation medium to model the dentine in the layer of enamel. Simulations are carried out for photons launched as pencil beam and broad beams of radius 0.1 cm, 0.2 cm, and 0.3 cm to study the best illumination pattern for the detection of dentine in the tooth. High-performance computing supercomputers are used to run the simulations in parallel, and the results are averaged for computational efficiency. The spatial location of generation of Raman photons is shown in two-dimension and one-dimension. The Raman photon intensity from the object (signal) and layer (noise) is recorded independently and the signal-to-noise is plotted. The signal intensity from the embedded sphere is high for 0.1 cm broad beam. The reproducibility of the broad beam is illustrated by performing the simulation for best illumination radius with different offsets from the origin along the x-axis.","PeriodicalId":262474,"journal":{"name":"2018 Fourth International Conference on Biosignals, Images and Instrumentation (ICBSII)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129370356","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}