Pub Date : 2021-10-25DOI: 10.1109/BIBE52308.2021.9635497
Ioan Sima, Kristijan Cincar
We used a deep learning model, called Inception V3, to classify colorectal polyps into: hyperplastic, serrated and adenoma lesions using colonoscopy images. Inception V3 is a convolution neural network (CNN) pre-trained on an extremely large dataset, which is based on multi-branch convolutional networks. Because we have a relative small dataset, we use transfer learning (TL) to transfer the optimal weights of hundreds of hours of training across multiple high-power GPUs. A dataset 152 instances containing 76 polyps belonging to the three lesion types was used. We re-trained the last five layers of Inception V3 with two-thirds of the images in the dataset. The results obtained with our new neural network model are satisfactory compared to other works and human experts.
{"title":"Transfer Learning-Based Classification of Gastrointestinal Polyps","authors":"Ioan Sima, Kristijan Cincar","doi":"10.1109/BIBE52308.2021.9635497","DOIUrl":"https://doi.org/10.1109/BIBE52308.2021.9635497","url":null,"abstract":"We used a deep learning model, called Inception V3, to classify colorectal polyps into: hyperplastic, serrated and adenoma lesions using colonoscopy images. Inception V3 is a convolution neural network (CNN) pre-trained on an extremely large dataset, which is based on multi-branch convolutional networks. Because we have a relative small dataset, we use transfer learning (TL) to transfer the optimal weights of hundreds of hours of training across multiple high-power GPUs. A dataset 152 instances containing 76 polyps belonging to the three lesion types was used. We re-trained the last five layers of Inception V3 with two-thirds of the images in the dataset. The results obtained with our new neural network model are satisfactory compared to other works and human experts.","PeriodicalId":343724,"journal":{"name":"2021 IEEE 21st International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"74 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"115719243","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 : 2021-10-25DOI: 10.1109/BIBE52308.2021.9635418
Fotis Konstantakopoulos, Eleni I. Georga, D. Fotiadis
It is generally accepted that a healthy diet plays an important role in modern lifestyle and can prevent or reduce the effects of important diseases, such as obesity, diabetes or cardiovascular diseases. Technological advancement and the wide spread of smartphones enable the monitoring and recording of nutritional habits on a daily basis, through mHealth solutions. The most difficult task of mHealth dietary systems for calculating the nutritional composition of food is to estimate its volume. In this study, we present a volume estimation system based on structure from motion smartphone camera, through two-view 3D food reconstruction. The proposed methodology uses stereo vision techniques and requires the input of two food images with a reference card next to the plate, to reconstruct the 3D structure of the food and to estimate its volume. The above approach achieves a mean absolute percentage error from 4.6 - 11.1% per food dish. The systematic collection of a labelled Mediterranean Greek Food images dataset, the MedGRFood, with known food weight allows the evaluation of the proposed methodology.
{"title":"3D Reconstruction and Volume Estimation of Food using Stereo Vision Techniques","authors":"Fotis Konstantakopoulos, Eleni I. Georga, D. Fotiadis","doi":"10.1109/BIBE52308.2021.9635418","DOIUrl":"https://doi.org/10.1109/BIBE52308.2021.9635418","url":null,"abstract":"It is generally accepted that a healthy diet plays an important role in modern lifestyle and can prevent or reduce the effects of important diseases, such as obesity, diabetes or cardiovascular diseases. Technological advancement and the wide spread of smartphones enable the monitoring and recording of nutritional habits on a daily basis, through mHealth solutions. The most difficult task of mHealth dietary systems for calculating the nutritional composition of food is to estimate its volume. In this study, we present a volume estimation system based on structure from motion smartphone camera, through two-view 3D food reconstruction. The proposed methodology uses stereo vision techniques and requires the input of two food images with a reference card next to the plate, to reconstruct the 3D structure of the food and to estimate its volume. The above approach achieves a mean absolute percentage error from 4.6 - 11.1% per food dish. The systematic collection of a labelled Mediterranean Greek Food images dataset, the MedGRFood, with known food weight allows the evaluation of the proposed methodology.","PeriodicalId":343724,"journal":{"name":"2021 IEEE 21st International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122789079","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 : 2021-10-25DOI: 10.1109/BIBE52308.2021.9635461
Muhammad Akmal, Muhammad Farrukh Qureshi, Faisal Amin, M. Z. Rehman, I. Niazi
In this work we applied real-time classification of prosthetic fingers movements using surface electromyography (sEMG) data. We employed support vector machine (SVM) for classification of fingers movements. SVM has some benefits over other classification techniques e.g. 1) it avoids overfitting, 2) handles nonlinear data efficiently and 3) it is stable. SVM is employed on Raspberry pi which is a low-cost, credit-card sized computer with high processing power. Moreover, it supports Python which makes it easy to build projects and it has multiple interfaces available. In this paper, our aim is to perform classification of prosthetic hand relative to human fingers. To assess the performance of our framework we tested it on ten healthy subjects. Our framework was able to achieve mean classification accuracy of 78%.
{"title":"SVM-based Real-Time Classification of Prosthetic Fingers using Myo Armband-acquired Electromyography Data","authors":"Muhammad Akmal, Muhammad Farrukh Qureshi, Faisal Amin, M. Z. Rehman, I. Niazi","doi":"10.1109/BIBE52308.2021.9635461","DOIUrl":"https://doi.org/10.1109/BIBE52308.2021.9635461","url":null,"abstract":"In this work we applied real-time classification of prosthetic fingers movements using surface electromyography (sEMG) data. We employed support vector machine (SVM) for classification of fingers movements. SVM has some benefits over other classification techniques e.g. 1) it avoids overfitting, 2) handles nonlinear data efficiently and 3) it is stable. SVM is employed on Raspberry pi which is a low-cost, credit-card sized computer with high processing power. Moreover, it supports Python which makes it easy to build projects and it has multiple interfaces available. In this paper, our aim is to perform classification of prosthetic hand relative to human fingers. To assess the performance of our framework we tested it on ten healthy subjects. Our framework was able to achieve mean classification accuracy of 78%.","PeriodicalId":343724,"journal":{"name":"2021 IEEE 21st International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"49 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"125316148","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 : 2021-10-25DOI: 10.1109/BIBE52308.2021.9635202
Dalel Ayed Lakhal, Saoussen Bel Hadj Kacem, M. Tagina, Mohamed Ali Amara
In the pharmaceutical industry, the production of psychiatric drugs has been seriously disrupted since the appearance of COVID'19. For that, Demand Forecasting of psychiatric drugs is among the big challenges in this industry. The objective is to avoid an excess of stock and, at the same time, to ensure that a stock rupture does not occur. Based on analysis of psychiatric drugs data, we compare in this paper several forecasting techniques which are Exponential Smoothing, seasonal ARIMA (i.e. SARIMA), SARIMAX, enhanced with the integration of exogenous (explanatory) variables, and LSTM. Through all the done tests, we make a comparison study of the results to identify the most promising models.
{"title":"Prediction of psychiatric drugs sale during COVID-19","authors":"Dalel Ayed Lakhal, Saoussen Bel Hadj Kacem, M. Tagina, Mohamed Ali Amara","doi":"10.1109/BIBE52308.2021.9635202","DOIUrl":"https://doi.org/10.1109/BIBE52308.2021.9635202","url":null,"abstract":"In the pharmaceutical industry, the production of psychiatric drugs has been seriously disrupted since the appearance of COVID'19. For that, Demand Forecasting of psychiatric drugs is among the big challenges in this industry. The objective is to avoid an excess of stock and, at the same time, to ensure that a stock rupture does not occur. Based on analysis of psychiatric drugs data, we compare in this paper several forecasting techniques which are Exponential Smoothing, seasonal ARIMA (i.e. SARIMA), SARIMAX, enhanced with the integration of exogenous (explanatory) variables, and LSTM. Through all the done tests, we make a comparison study of the results to identify the most promising models.","PeriodicalId":343724,"journal":{"name":"2021 IEEE 21st International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"113 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116108395","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 : 2021-10-25DOI: 10.1109/BIBE52308.2021.9635373
M. Antonijević, Dušica M Simijonović, D. Milenkovic, Z. Marković
Carbonic anhydrase isoforms IX and XII are crucial for the regulation of extracellular pH thus facilitating cancer cell proliferation, invasion, and metastasis. Therefore, discovering good inhibitors of CA-IX and CA-XII is of great importance. In this study, the inhibitory activity of previously synthesized coumarin-hydroxybenzohydrazide 3a and its parent molecule 4-hydroxycoumarin, against enzymes CA-IX and CA-XII was investigated. For that purpose, the molecular docking study was performed. The activity of both investigated compounds was calculated for neutral and anionic species. The obtained results indicate that compound 3a expresses good inhibitory activity towards both investigated enzymes, but inhibitory activity is significantly better towards CA-XII than CA-IX.
{"title":"Molecular docking study of coumarin-hydroxybenzohydrazide hybrid as an inhibitor of carbonic anhydrases IX and XII","authors":"M. Antonijević, Dušica M Simijonović, D. Milenkovic, Z. Marković","doi":"10.1109/BIBE52308.2021.9635373","DOIUrl":"https://doi.org/10.1109/BIBE52308.2021.9635373","url":null,"abstract":"Carbonic anhydrase isoforms IX and XII are crucial for the regulation of extracellular pH thus facilitating cancer cell proliferation, invasion, and metastasis. Therefore, discovering good inhibitors of CA-IX and CA-XII is of great importance. In this study, the inhibitory activity of previously synthesized coumarin-hydroxybenzohydrazide 3a and its parent molecule 4-hydroxycoumarin, against enzymes CA-IX and CA-XII was investigated. For that purpose, the molecular docking study was performed. The activity of both investigated compounds was calculated for neutral and anionic species. The obtained results indicate that compound 3a expresses good inhibitory activity towards both investigated enzymes, but inhibitory activity is significantly better towards CA-XII than CA-IX.","PeriodicalId":343724,"journal":{"name":"2021 IEEE 21st International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"116529585","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 : 2021-10-25DOI: 10.1109/BIBE52308.2021.9635356
J. Opfermann, Benjamin Killeen, Christopher Bailey, Majid Khan, A. Uneri, Kensei Suzuki, M. Armand, F. Hui, A. Krieger, M. Unberath
Vertebral compression fractures (VCFs), the most common fragility fractures secondary to osteoporosis, affect more than 200 million individuals worldwide. Percutaneous vertebral augmentation is an effective interventional treatment option that is routinely performed across the world. Because fluoroscopy-guided vertebral augmentation is a well-established and safe minimally invasive technique, automating its delivery is among the most important next steps. In this work, we describe the design and evaluation of a novel cannula mounted vertebral augmentation robot in a simulated X-ray environment as a first step toward autonomous vertebral augmentation. The cannula robot employs a piezo stack with inchworm control to place surgical tools within the vertebral body, while X-ray imaging verifies the robot does not interfere with imaging. Finite element analysis of the robot confirms that radiolucent materials were rigid enough to be used in the robot design as expected deformations for the cannula drive, accessory drive, and locking mechanisms $(1.299 pm 0.034 um, 1.280 pm 0.027 um$, and $1.960 pm 0.218 um$, respectively) did not exceed the stroke lengths of the piezo stacks. An in silico clinical trial based on a human anatomy model suffering from VCF validates that the cannula robot does not impede visualization of the critical anatomy and tool-to-tissue positioning. Together these results demonstrate the feasibility of a cannula mounted robot for vertebral augmentation.
{"title":"Feasibility of a Cannula-Mounted Piezo Robot for Image-Guided Vertebral Augmentation: Toward a Low Cost, Semi-Autonomous Approach","authors":"J. Opfermann, Benjamin Killeen, Christopher Bailey, Majid Khan, A. Uneri, Kensei Suzuki, M. Armand, F. Hui, A. Krieger, M. Unberath","doi":"10.1109/BIBE52308.2021.9635356","DOIUrl":"https://doi.org/10.1109/BIBE52308.2021.9635356","url":null,"abstract":"Vertebral compression fractures (VCFs), the most common fragility fractures secondary to osteoporosis, affect more than 200 million individuals worldwide. Percutaneous vertebral augmentation is an effective interventional treatment option that is routinely performed across the world. Because fluoroscopy-guided vertebral augmentation is a well-established and safe minimally invasive technique, automating its delivery is among the most important next steps. In this work, we describe the design and evaluation of a novel cannula mounted vertebral augmentation robot in a simulated X-ray environment as a first step toward autonomous vertebral augmentation. The cannula robot employs a piezo stack with inchworm control to place surgical tools within the vertebral body, while X-ray imaging verifies the robot does not interfere with imaging. Finite element analysis of the robot confirms that radiolucent materials were rigid enough to be used in the robot design as expected deformations for the cannula drive, accessory drive, and locking mechanisms $(1.299 pm 0.034 um, 1.280 pm 0.027 um$, and $1.960 pm 0.218 um$, respectively) did not exceed the stroke lengths of the piezo stacks. An in silico clinical trial based on a human anatomy model suffering from VCF validates that the cannula robot does not impede visualization of the critical anatomy and tool-to-tissue positioning. Together these results demonstrate the feasibility of a cannula mounted robot for vertebral augmentation.","PeriodicalId":343724,"journal":{"name":"2021 IEEE 21st International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126778480","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 : 2021-10-25DOI: 10.1109/BIBE52308.2021.9635185
Jelena Đorović Jovanović, Z. Marković, Mihajlo Kokanovic, Nenad Filipović, M. S. Pirkovic
Heart failure (HF) is a condition that affects mostly older populations. It can be treated with different medications, and one of them is Entresto. This is a medication which is consisting of two drugs, sacubitril (SAC) and valsartan (VAL). Here, in this study, are performed molecular docking simulations in order to examine the inhibitory potency of SAC and VAL towards neprilysin (NEP) and angiotensin II receptor (AT2), respectively. The achieved thermodynamic parameters shows that SAC and VAL can bind to targeted protein, and inhibit NEP and AT2. The best binding sites are determined. Also, the amino acids responsible for binding are identified.
{"title":"Inhibitory potency of Valsartan/Sacubitril drug combination: molecular docking simulations","authors":"Jelena Đorović Jovanović, Z. Marković, Mihajlo Kokanovic, Nenad Filipović, M. S. Pirkovic","doi":"10.1109/BIBE52308.2021.9635185","DOIUrl":"https://doi.org/10.1109/BIBE52308.2021.9635185","url":null,"abstract":"Heart failure (HF) is a condition that affects mostly older populations. It can be treated with different medications, and one of them is Entresto. This is a medication which is consisting of two drugs, sacubitril (SAC) and valsartan (VAL). Here, in this study, are performed molecular docking simulations in order to examine the inhibitory potency of SAC and VAL towards neprilysin (NEP) and angiotensin II receptor (AT2), respectively. The achieved thermodynamic parameters shows that SAC and VAL can bind to targeted protein, and inhibit NEP and AT2. The best binding sites are determined. Also, the amino acids responsible for binding are identified.","PeriodicalId":343724,"journal":{"name":"2021 IEEE 21st International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"96 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134304408","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 : 2021-10-25DOI: 10.1109/BIBE52308.2021.9635307
Lamija Hafizović, Aldijana Čaušević, Amar Deumic, L. S. Becirovic, L. G. Pokvic, A. Badnjević
Diagnostic medical imaging and the interpretation of the imaging results pose a great challenge for the medical profession as the final conclusions are highly susceptible to human error and subjectivity. The necessity for standardization of interpretation of medical images is very necessary to bypass these problems. The only way of achieving this is using a methodology which excludes the human eye and employs artificial intelligence. However, another challenge is selecting the most suitable AI algorithm fit for the challenging task of imaging results interpretation. This study was conducted following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines published in 2020. Research was done using PubMed, ScienceDirect and Google Scholar databases where the key inclusion criteria were language, journal credibility, open access to full-text publications and the most recent papers. In order to focus on only the most recent research, only the papers published in the last 5 years were evaluated. The search through PubMed, ScienceDirect and Google Scholar has yielded 81, 205, and 520 papers respectively. Out of this number of papers, 26 of them have met all of the inclusion criteria and were included in the research. The observed accuracies of the models and the overall rising interest in the topic denote that this field is rapidly growing and has a great potential to be applied in daily medical practice in the future.
{"title":"The Use of Artificial Intelligence in Diagnostic Medical Imaging: Systematic Literature Review","authors":"Lamija Hafizović, Aldijana Čaušević, Amar Deumic, L. S. Becirovic, L. G. Pokvic, A. Badnjević","doi":"10.1109/BIBE52308.2021.9635307","DOIUrl":"https://doi.org/10.1109/BIBE52308.2021.9635307","url":null,"abstract":"Diagnostic medical imaging and the interpretation of the imaging results pose a great challenge for the medical profession as the final conclusions are highly susceptible to human error and subjectivity. The necessity for standardization of interpretation of medical images is very necessary to bypass these problems. The only way of achieving this is using a methodology which excludes the human eye and employs artificial intelligence. However, another challenge is selecting the most suitable AI algorithm fit for the challenging task of imaging results interpretation. This study was conducted following PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines published in 2020. Research was done using PubMed, ScienceDirect and Google Scholar databases where the key inclusion criteria were language, journal credibility, open access to full-text publications and the most recent papers. In order to focus on only the most recent research, only the papers published in the last 5 years were evaluated. The search through PubMed, ScienceDirect and Google Scholar has yielded 81, 205, and 520 papers respectively. Out of this number of papers, 26 of them have met all of the inclusion criteria and were included in the research. The observed accuracies of the models and the overall rising interest in the topic denote that this field is rapidly growing and has a great potential to be applied in daily medical practice in the future.","PeriodicalId":343724,"journal":{"name":"2021 IEEE 21st International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"62 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132640386","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 : 2021-10-25DOI: 10.1109/BIBE52308.2021.9635525
T. DeRamus, A. Iraji, Z. Fu, Rogers F. Silva, J. Stephen, T. Wilson, Yu Ping Wang, Yuhui Du, Jingyu Liu, V. Calhoun
The reliability of functional network connectivity (FNC) measured using independent component analysis (ICA) has frequently been explored within the literature, with results displaying varying levels of reliability and demonstrating that minor changes in data preprocessing procedures can significantly alter FC results and reliability. However, one important avenue of research that has not been explored within the current literature is the effect of spatial normalization techniques on FNC reliability. Spatially constrained independent component analysis techniques such as multi-objective optimization with reference (MOO-ICAR) is one of many methods used to study brain functional connectivity (FC) using fMRI that is theoretically robust to variations which may arise in data as a result of normalization procedures. In this work, we deploy MOO-ICAR across 30 different spatial normalization pipelines varying across participant template, normalization modality (anatomical vs functional), and one vs. two-stage warps to MNI space. Most components display relatively high consistency intraclass-correlation coefficients (ICCs), with the vast majoritv (~80%) ereater than 0.5.
{"title":"Stability of functional network connectivity (FNC) values across multiple spatial normalization pipelines in spatially constrained independent component analysis","authors":"T. DeRamus, A. Iraji, Z. Fu, Rogers F. Silva, J. Stephen, T. Wilson, Yu Ping Wang, Yuhui Du, Jingyu Liu, V. Calhoun","doi":"10.1109/BIBE52308.2021.9635525","DOIUrl":"https://doi.org/10.1109/BIBE52308.2021.9635525","url":null,"abstract":"The reliability of functional network connectivity (FNC) measured using independent component analysis (ICA) has frequently been explored within the literature, with results displaying varying levels of reliability and demonstrating that minor changes in data preprocessing procedures can significantly alter FC results and reliability. However, one important avenue of research that has not been explored within the current literature is the effect of spatial normalization techniques on FNC reliability. Spatially constrained independent component analysis techniques such as multi-objective optimization with reference (MOO-ICAR) is one of many methods used to study brain functional connectivity (FC) using fMRI that is theoretically robust to variations which may arise in data as a result of normalization procedures. In this work, we deploy MOO-ICAR across 30 different spatial normalization pipelines varying across participant template, normalization modality (anatomical vs functional), and one vs. two-stage warps to MNI space. Most components display relatively high consistency intraclass-correlation coefficients (ICCs), with the vast majoritv (~80%) ereater than 0.5.","PeriodicalId":343724,"journal":{"name":"2021 IEEE 21st International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122341671","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 : 2021-10-25DOI: 10.1109/BIBE52308.2021.9635408
B. Milićević, M. Milošević, V. Simić, D. Trifunovic, N. Filipovic, M. Kojic
Most cardiac diseases and disorders occur in the left ventricle. Numerical methods can give an insight into the mechanical response of the left ventricle under different conditions, before the execution of clinical trials and experiments. Before we use the finite element method to analyze the behavior of the left ventricle, a geometrical model has to be generated. In our work, we generated a left ventricle model from echocardiographic data. We manually extracted contours of the inner and outer surface of the left ventricle and applied our algorithm to generate the 3D model. This semi-automatic model generation enables the usage of patient-specific geometries for finite element analysis of the left ventricle.
{"title":"Semi-Automatic Left Ventricle Model Generation","authors":"B. Milićević, M. Milošević, V. Simić, D. Trifunovic, N. Filipovic, M. Kojic","doi":"10.1109/BIBE52308.2021.9635408","DOIUrl":"https://doi.org/10.1109/BIBE52308.2021.9635408","url":null,"abstract":"Most cardiac diseases and disorders occur in the left ventricle. Numerical methods can give an insight into the mechanical response of the left ventricle under different conditions, before the execution of clinical trials and experiments. Before we use the finite element method to analyze the behavior of the left ventricle, a geometrical model has to be generated. In our work, we generated a left ventricle model from echocardiographic data. We manually extracted contours of the inner and outer surface of the left ventricle and applied our algorithm to generate the 3D model. This semi-automatic model generation enables the usage of patient-specific geometries for finite element analysis of the left ventricle.","PeriodicalId":343724,"journal":{"name":"2021 IEEE 21st International Conference on Bioinformatics and Bioengineering (BIBE)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2021-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"122589349","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}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：