Pub Date : 2014-11-01DOI: 10.1109/ICBME.2014.7043899
Razieh Falahian, M. M. Dastjerdi, S. Gharibzadeh
The Modeling of the behavior of biological systems, together with their responses to various internal and external stimuli plays a paramount role in accurate perception, analysis, control and prediction of their behaviors. Every Biological system is an extremely complex nonlinear system. This characteristic is the consequence of the complicated interactions within various components of the system as well as with its environment. The outcomes of recent investigations have indicated that the majority of biological systems tend to behave in chaotic patterns. The result of our study points out that the response of the brain to some stimuli such as the flicker light is an exemplar of such demeanor. The requisite remains, however, for realistic modeling of this specific behavior of the brain. In this paper, we represent the results of modeling this special chaotic response of the brain by utilizing multilayer feed-forward neural network. In pursuance of evaluating our model, we employ some electroretinogram data. The capability of the specified neural network to model this complex behavior is indeed confirmed.
{"title":"Novel insight into modeling of brain response to flicker light","authors":"Razieh Falahian, M. M. Dastjerdi, S. Gharibzadeh","doi":"10.1109/ICBME.2014.7043899","DOIUrl":"https://doi.org/10.1109/ICBME.2014.7043899","url":null,"abstract":"The Modeling of the behavior of biological systems, together with their responses to various internal and external stimuli plays a paramount role in accurate perception, analysis, control and prediction of their behaviors. Every Biological system is an extremely complex nonlinear system. This characteristic is the consequence of the complicated interactions within various components of the system as well as with its environment. The outcomes of recent investigations have indicated that the majority of biological systems tend to behave in chaotic patterns. The result of our study points out that the response of the brain to some stimuli such as the flicker light is an exemplar of such demeanor. The requisite remains, however, for realistic modeling of this specific behavior of the brain. In this paper, we represent the results of modeling this special chaotic response of the brain by utilizing multilayer feed-forward neural network. In pursuance of evaluating our model, we employ some electroretinogram data. The capability of the specified neural network to model this complex behavior is indeed confirmed.","PeriodicalId":434822,"journal":{"name":"2014 21th Iranian Conference on Biomedical Engineering (ICBME)","volume":"41 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132475350","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}
Pub Date : 2014-11-01DOI: 10.1109/ICBME.2014.7043886
Danial Sharifikia, M. Asgari
Simulation of human heart mitral valves is a challenging biomechanical problem due to its complex anatomical structure, material properties and time dependent loading conditions. This study presents a modeling and simulation of human mitral valve behavior considering the effects of material nonlinearity and Chordae tendineae rupture via a numerical analysis. Three-dimensional sized geometrical model obtained from anatomically measurement used as structural model The transient finite element method including inertia effects and time dependencies implemented for numerical solution. Two different material models have been considered to illustrate the effect of material nonlinearity on the stress and strain imposed by leaflets. On the other hand Chordae tendineae rupture caused by bacterial endocarditis, rheumatic valvular disease or trauma can be a deadly defect leads to malfunction of human heart. Chordae tendineae rupture has been also simulated to investigate the effects on leaflet stresses and strains. Based on the results, although the linear elastic model exhibits an acceptable correlation in the location of high stress regions with the hyperelastic model but Stress magnitudes differ between the elastic and hyper elastic model Depending on the strain energy function used to describe the nonlinear material, different stress magnitudes release from the analyses. Chordae rupture causes an unintended increase in the magnitude of leaflet stresses and the closed valve configuration. The increment value depends on the location and number of ruptured chordae.
{"title":"Structural simulation of human mitral valve behaviour cosidering effects of material nonlinearities","authors":"Danial Sharifikia, M. Asgari","doi":"10.1109/ICBME.2014.7043886","DOIUrl":"https://doi.org/10.1109/ICBME.2014.7043886","url":null,"abstract":"Simulation of human heart mitral valves is a challenging biomechanical problem due to its complex anatomical structure, material properties and time dependent loading conditions. This study presents a modeling and simulation of human mitral valve behavior considering the effects of material nonlinearity and Chordae tendineae rupture via a numerical analysis. Three-dimensional sized geometrical model obtained from anatomically measurement used as structural model The transient finite element method including inertia effects and time dependencies implemented for numerical solution. Two different material models have been considered to illustrate the effect of material nonlinearity on the stress and strain imposed by leaflets. On the other hand Chordae tendineae rupture caused by bacterial endocarditis, rheumatic valvular disease or trauma can be a deadly defect leads to malfunction of human heart. Chordae tendineae rupture has been also simulated to investigate the effects on leaflet stresses and strains. Based on the results, although the linear elastic model exhibits an acceptable correlation in the location of high stress regions with the hyperelastic model but Stress magnitudes differ between the elastic and hyper elastic model Depending on the strain energy function used to describe the nonlinear material, different stress magnitudes release from the analyses. Chordae rupture causes an unintended increase in the magnitude of leaflet stresses and the closed valve configuration. The increment value depends on the location and number of ruptured chordae.","PeriodicalId":434822,"journal":{"name":"2014 21th Iranian Conference on Biomedical Engineering (ICBME)","volume":"33 7","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132934164","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}
Pub Date : 2014-11-01DOI: 10.1109/ICBME.2014.7043895
Roozbeh Atri, M. Mohebbi
Sleep apnea is a frequent disorder where breathing process is ceased during the sleep and it is found to be a root for cardiovascular problems. In this study, we tend to detect this syndrome solely from nocturnal ECG records. The proposed method is based on higher order spectrum of heart rate variability (HRV) and ECG-derived respiratory (EDR) signals, which extracted from ECG signal. In order to use quadratic phase coupled harmonics information emerging from non-linearities of the HRV and EDR signals, their bispectral features had been employed. Moreover, these features are complemented by time-domain features which can map the signal irregularities. A least square support vector machine (LS-SVM) classifier has been used to detect apneic episodes. The performance of the proposed method is studied using a publicly available database of Physionet. It is shown that the achieved sensitivity, specificity, and accuracy of the presented method were 90.21%, 86.21%, and 88.21%, respectively.
{"title":"Screening of obstructive sleep apnea using higher order statistics of HRV and EDR signals","authors":"Roozbeh Atri, M. Mohebbi","doi":"10.1109/ICBME.2014.7043895","DOIUrl":"https://doi.org/10.1109/ICBME.2014.7043895","url":null,"abstract":"Sleep apnea is a frequent disorder where breathing process is ceased during the sleep and it is found to be a root for cardiovascular problems. In this study, we tend to detect this syndrome solely from nocturnal ECG records. The proposed method is based on higher order spectrum of heart rate variability (HRV) and ECG-derived respiratory (EDR) signals, which extracted from ECG signal. In order to use quadratic phase coupled harmonics information emerging from non-linearities of the HRV and EDR signals, their bispectral features had been employed. Moreover, these features are complemented by time-domain features which can map the signal irregularities. A least square support vector machine (LS-SVM) classifier has been used to detect apneic episodes. The performance of the proposed method is studied using a publicly available database of Physionet. It is shown that the achieved sensitivity, specificity, and accuracy of the presented method were 90.21%, 86.21%, and 88.21%, respectively.","PeriodicalId":434822,"journal":{"name":"2014 21th Iranian Conference on Biomedical Engineering (ICBME)","volume":"28 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134347903","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}
Pub Date : 2014-11-01DOI: 10.1109/ICBME.2014.7043934
Solmaz Abbasi, Farshad Tajeri pour
In this paper, a method for 3D medical image segmentation is presented. This method is used to detect brain tumor in MRI images by combining Clustering and Classification methods to decrease the complexity of time and memory. In the first phase, non-negative matrix factorization with sparseness constraint method is used to separate the region of interest from the image. In the second phase, the classification of the region of interest is performed. For this purpose, TOP-LBP features and gray level co-occurrence matrix are extracted and Random forest is used for classification and segmentation of the necrosis, edema, non-enhanced tumor and enhanced tumor. This method has achieved a fast speed for segmentation of MRI 3D images and has been evaluated with criteria of Dice's and Jacquard's coefficient on the brain tumor from magnetic resonance image obtained from the Brats2013 database.
{"title":"A hybrid approach for detection of brain tumor in MRI images","authors":"Solmaz Abbasi, Farshad Tajeri pour","doi":"10.1109/ICBME.2014.7043934","DOIUrl":"https://doi.org/10.1109/ICBME.2014.7043934","url":null,"abstract":"In this paper, a method for 3D medical image segmentation is presented. This method is used to detect brain tumor in MRI images by combining Clustering and Classification methods to decrease the complexity of time and memory. In the first phase, non-negative matrix factorization with sparseness constraint method is used to separate the region of interest from the image. In the second phase, the classification of the region of interest is performed. For this purpose, TOP-LBP features and gray level co-occurrence matrix are extracted and Random forest is used for classification and segmentation of the necrosis, edema, non-enhanced tumor and enhanced tumor. This method has achieved a fast speed for segmentation of MRI 3D images and has been evaluated with criteria of Dice's and Jacquard's coefficient on the brain tumor from magnetic resonance image obtained from the Brats2013 database.","PeriodicalId":434822,"journal":{"name":"2014 21th Iranian Conference on Biomedical Engineering (ICBME)","volume":"140 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115810984","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}
Pub Date : 2014-11-01DOI: 10.1109/ICBME.2014.7043894
A. Taymourtash, F. Ghassemi
In this study, an improved method of iterative independent component analysis (iICA) on single-trial brain responses was employed to investigate neural mechanisms underlying inhibitory control deficits in adults with attention deficit / hyperactivity disorder (ADHD). Specially recorded data during a continuous performance task from 10 ADHD and 11 healthy control subjects were analyzed. Behavioral measures showed that the inconsistency in response speed were significantly greater in adults with ADHD compared to control subjects (p = 0.009). ERP data revealed ADHD group compared to healthy controls had a significant increase in N2 amplitudes while P3 amplitudes' decreased particularly for shorter inter-stimulus intervals. Furthermore, N2 amplitude correlated with the number of ADHD symptoms. These results confirm the utility of the iICA method in discrimination between adults with ADHD and healthy comparison controls and strongly suggest that this method can be used for further evaluation of cognitive functioning.
{"title":"Neurophysiological correlates of inhibitory control in adults with ADHD revealed by iterative independent component analysis","authors":"A. Taymourtash, F. Ghassemi","doi":"10.1109/ICBME.2014.7043894","DOIUrl":"https://doi.org/10.1109/ICBME.2014.7043894","url":null,"abstract":"In this study, an improved method of iterative independent component analysis (iICA) on single-trial brain responses was employed to investigate neural mechanisms underlying inhibitory control deficits in adults with attention deficit / hyperactivity disorder (ADHD). Specially recorded data during a continuous performance task from 10 ADHD and 11 healthy control subjects were analyzed. Behavioral measures showed that the inconsistency in response speed were significantly greater in adults with ADHD compared to control subjects (p = 0.009). ERP data revealed ADHD group compared to healthy controls had a significant increase in N2 amplitudes while P3 amplitudes' decreased particularly for shorter inter-stimulus intervals. Furthermore, N2 amplitude correlated with the number of ADHD symptoms. These results confirm the utility of the iICA method in discrimination between adults with ADHD and healthy comparison controls and strongly suggest that this method can be used for further evaluation of cognitive functioning.","PeriodicalId":434822,"journal":{"name":"2014 21th Iranian Conference on Biomedical Engineering (ICBME)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122615384","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}
Pub Date : 2014-11-01DOI: 10.1109/ICBME.2014.7043896
Maryam Moghadam, M. Moradi
Blood Pressure (BP) measurement during exercise test is of great importance. Due to the low accuracy of measuring BP using cuff and barometer during exercise and limitations in the continuous measurements because of the vessel crush, it will be of great advantage to obtain systolic and diastolic BP values in a cuff-less approach. This could be achieved by using extracted features and characteristics of ECG and PPG signals. BP is highly correlated with features such as PTT and HR. However, the correlation is not necessarily linear. It could be nonlinear, multimodal and vague. Therefore, the use of fuzzy function approach with the parameters used in physiological models as its inputs is proposed in this paper. Then, in order to improve the performance of fuzzy function to estimate BP, GK clustering method instead of the FCM and LS-SVM instead of LSE are used in order to produce the antecedent and consequent of the rules respectively. Comparing the results with the BP values which are estimated using NN, and fuzzy systems based on GD training and RLS, indicate better performance of modified fuzzy function with approximately zero mean error and less or almost equal to 8 mmHg as the value of STD in satisfying AAMI standard in systolic and diastolic BP estimation of all stages.
{"title":"Model based Blood Pressure estimation during exercise test using modified fuzzy function","authors":"Maryam Moghadam, M. Moradi","doi":"10.1109/ICBME.2014.7043896","DOIUrl":"https://doi.org/10.1109/ICBME.2014.7043896","url":null,"abstract":"Blood Pressure (BP) measurement during exercise test is of great importance. Due to the low accuracy of measuring BP using cuff and barometer during exercise and limitations in the continuous measurements because of the vessel crush, it will be of great advantage to obtain systolic and diastolic BP values in a cuff-less approach. This could be achieved by using extracted features and characteristics of ECG and PPG signals. BP is highly correlated with features such as PTT and HR. However, the correlation is not necessarily linear. It could be nonlinear, multimodal and vague. Therefore, the use of fuzzy function approach with the parameters used in physiological models as its inputs is proposed in this paper. Then, in order to improve the performance of fuzzy function to estimate BP, GK clustering method instead of the FCM and LS-SVM instead of LSE are used in order to produce the antecedent and consequent of the rules respectively. Comparing the results with the BP values which are estimated using NN, and fuzzy systems based on GD training and RLS, indicate better performance of modified fuzzy function with approximately zero mean error and less or almost equal to 8 mmHg as the value of STD in satisfying AAMI standard in systolic and diastolic BP estimation of all stages.","PeriodicalId":434822,"journal":{"name":"2014 21th Iranian Conference on Biomedical Engineering (ICBME)","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125186999","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}
Pub Date : 2014-11-01DOI: 10.1109/ICBME.2014.7043933
Mohsen Bahramf, G. Hossein-Zadeh
There is a growing trend in the application of graph analysis to resting-state fMRI data. In such studies, vertices of the graph represent brain regions, and graph edges represent the connectivity between them. Regions are usually defined using anatomical atlases. In this paper we show that using functional parcellation which is considered to be better than anatomical segmentation causes differences in network measures of resting-state fMRI (rs-fMRI) graphs. In this study we used an anatomical atlas (AAL) and three functional parcellations with 98, 183, and 376 parcels for defining the brain regions in rs-fMRI data. Based on each, a functional connectivity graph is constructed and common network measures such as clustering coefficient, and characteristic-path length are calculated over 25 rs-fMRI data. Results indicate that networks obtained through functional parcellations have small world property at all resolutions. Correlation between network measures showed that characteristic path length in AAL-based network and parcellation-driven networks are noticeably different. This paper provides quantitative evidence on how using a functional parcellation, created from the functional data, can affect the measures that show the functional organization of the brain.
{"title":"Functional parcellations affect the network measures in graph analysis of resting-state fMRI","authors":"Mohsen Bahramf, G. Hossein-Zadeh","doi":"10.1109/ICBME.2014.7043933","DOIUrl":"https://doi.org/10.1109/ICBME.2014.7043933","url":null,"abstract":"There is a growing trend in the application of graph analysis to resting-state fMRI data. In such studies, vertices of the graph represent brain regions, and graph edges represent the connectivity between them. Regions are usually defined using anatomical atlases. In this paper we show that using functional parcellation which is considered to be better than anatomical segmentation causes differences in network measures of resting-state fMRI (rs-fMRI) graphs. In this study we used an anatomical atlas (AAL) and three functional parcellations with 98, 183, and 376 parcels for defining the brain regions in rs-fMRI data. Based on each, a functional connectivity graph is constructed and common network measures such as clustering coefficient, and characteristic-path length are calculated over 25 rs-fMRI data. Results indicate that networks obtained through functional parcellations have small world property at all resolutions. Correlation between network measures showed that characteristic path length in AAL-based network and parcellation-driven networks are noticeably different. This paper provides quantitative evidence on how using a functional parcellation, created from the functional data, can affect the measures that show the functional organization of the brain.","PeriodicalId":434822,"journal":{"name":"2014 21th Iranian Conference on Biomedical Engineering (ICBME)","volume":"13 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116033070","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}
Pub Date : 2014-11-01DOI: 10.1109/ICBME.2014.7043917
F. Abdolali, R. Zoroofi
We present a novel approach for modeling mandible shape variations in Temporomandibular Joint Osteoarthritis (TMJ OA) patients. We have employed weighted spherical harmonic (SPHARM) representation to parameterize and normalize mandible surfaces. This representation is fed to multivariate linear models which account for nuisance covariates such as age and mandible size. Multivariate linear models are implemented using SurfStat package and using this implementation one can avoid the complexity of specifying design matrices. In several multivariate shape models, the Hotelling's T-square has been used as a test statistic. In Hotelling's T-square statistic, we can test the equality of vector means without considering redundant covariates. Thus we have used SurfStat package in which Hotelling's T-square framework is generalized to incorporate additional covariates. Our proposed methodology has been applied for investigating Mandibular condyle shape variations in 19 TMJ OA subjects. Promising results have been demonstrated in lesion localization which is an important step in surgical planning and treatment.
{"title":"General multivariate linear modeling of mandible surface using SurfStat","authors":"F. Abdolali, R. Zoroofi","doi":"10.1109/ICBME.2014.7043917","DOIUrl":"https://doi.org/10.1109/ICBME.2014.7043917","url":null,"abstract":"We present a novel approach for modeling mandible shape variations in Temporomandibular Joint Osteoarthritis (TMJ OA) patients. We have employed weighted spherical harmonic (SPHARM) representation to parameterize and normalize mandible surfaces. This representation is fed to multivariate linear models which account for nuisance covariates such as age and mandible size. Multivariate linear models are implemented using SurfStat package and using this implementation one can avoid the complexity of specifying design matrices. In several multivariate shape models, the Hotelling's T-square has been used as a test statistic. In Hotelling's T-square statistic, we can test the equality of vector means without considering redundant covariates. Thus we have used SurfStat package in which Hotelling's T-square framework is generalized to incorporate additional covariates. Our proposed methodology has been applied for investigating Mandibular condyle shape variations in 19 TMJ OA subjects. Promising results have been demonstrated in lesion localization which is an important step in surgical planning and treatment.","PeriodicalId":434822,"journal":{"name":"2014 21th Iranian Conference on Biomedical Engineering (ICBME)","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"117349144","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}
Pub Date : 2014-11-01DOI: 10.1109/ICBME.2014.7043918
Hadi Soltanizadeh, Setareh Rezaee Oshterinan
Intracoronary optical coherence tomography (OCT) is a catheter based medical imaging technique that provide high resolution imaging of coronary lumen structures. However these images affected by catheter and stents shadows during pullback procedure. In order to overcome this problem, we present a new approach to detect the lumen boundary automatically using fuzzy system. At the first, the OCT images are mapped into the normalized polar OCT (NPOCT) space, and then primal lumen boundary is estimated by image processing methods. Afterwards, lumen boundary is detected by a fuzzy system precisely. Finally the results are remapped into the OCT image space. The proposed approach is compared with manual lumen detection (MLD), and HD and AD distance results are obtained.
{"title":"A new method for automatic lumen detection in intracoronary OCT images","authors":"Hadi Soltanizadeh, Setareh Rezaee Oshterinan","doi":"10.1109/ICBME.2014.7043918","DOIUrl":"https://doi.org/10.1109/ICBME.2014.7043918","url":null,"abstract":"Intracoronary optical coherence tomography (OCT) is a catheter based medical imaging technique that provide high resolution imaging of coronary lumen structures. However these images affected by catheter and stents shadows during pullback procedure. In order to overcome this problem, we present a new approach to detect the lumen boundary automatically using fuzzy system. At the first, the OCT images are mapped into the normalized polar OCT (NPOCT) space, and then primal lumen boundary is estimated by image processing methods. Afterwards, lumen boundary is detected by a fuzzy system precisely. Finally the results are remapped into the OCT image space. The proposed approach is compared with manual lumen detection (MLD), and HD and AD distance results are obtained.","PeriodicalId":434822,"journal":{"name":"2014 21th Iranian Conference on Biomedical Engineering (ICBME)","volume":"447 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122153275","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}
Pub Date : 2014-11-01DOI: 10.1109/ICBME.2014.7043919
M. Babaee, A. Nilchi
Image processing softwares, like all softwares, need to be both verified and validated. Synthetic images are very useful during the medical software development process to verify the accuracy of algorithms. In this paper we introduce the process of generating synthetic 2D medical X-ray images in addition to ground truth imaging parameters. First, a 3D model of an organ (e.g., vessels) is made in a 3D-modeling software. Then, this volume model is voxelized based on the specified resolution in order to create a 3D CT image of that organ by assigning proper Hounsfield unit to each voxel. The obtained 3D CT image volume is used in DRR program as the input. Geometry parameters such as internal and external parameters are adjusted to take some images from different views. We demonstrated this process by three examples to confirm its usage in validation of medical image processing applications.
{"title":"Synthetic data generation for X-ray imaging","authors":"M. Babaee, A. Nilchi","doi":"10.1109/ICBME.2014.7043919","DOIUrl":"https://doi.org/10.1109/ICBME.2014.7043919","url":null,"abstract":"Image processing softwares, like all softwares, need to be both verified and validated. Synthetic images are very useful during the medical software development process to verify the accuracy of algorithms. In this paper we introduce the process of generating synthetic 2D medical X-ray images in addition to ground truth imaging parameters. First, a 3D model of an organ (e.g., vessels) is made in a 3D-modeling software. Then, this volume model is voxelized based on the specified resolution in order to create a 3D CT image of that organ by assigning proper Hounsfield unit to each voxel. The obtained 3D CT image volume is used in DRR program as the input. Geometry parameters such as internal and external parameters are adjusted to take some images from different views. We demonstrated this process by three examples to confirm its usage in validation of medical image processing applications.","PeriodicalId":434822,"journal":{"name":"2014 21th Iranian Conference on Biomedical Engineering (ICBME)","volume":"68 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2014-11-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128102510","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}
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