TY  - CHAP
AU  - Peulić, Aleksandar S.
AU  - Milanković, Ivan
AU  - Mijailović, Nikola V.
AU  - Filipović, Nenad
PY  - 2019
UR  - http://gery.gef.bg.ac.rs/handle/123456789/1383
AB  - Image segmentation is one of the most common procedures in medical imaging applications. It is also very important task in breast cancer detection. Breast cancer detection procedure based on mammography can be divided into several stages. The first stage is the extraction of region of interest from a breast image, after which the identification of suspicious mass regions, their classification, and comparison with the existing image database follows. It is often the case that already existing image databases have large sets of data for which processing requires a lot of time, thus the acceleration of each of the processing stages in breast cancer detection is a very important issue. Image filtering is also one of the most common and important tasks in image processing applications. It is, in most cases, preprocessing procedure for 3D visualization of an image stack. In order to achieve high-quality 3D visualization of a 2D image stack, it is of particular importance that all the images of the input stack are clear and sharp, thus their filtering should be executed carefully. There are also many algorithms for 3D visualization, so it is important to choose the right one which will execute fast enough and produce satisfied quality. In this chapter, the implementation of the already existing algorithm for region-of-interest-based image segmentation for mammogram images on High-Performance Reconfigurable DataFlow Computers (HPRDC) is proposed. As a DataFlow Engine (DFE) of such HPRDC, Maxeler’s acceleration card is used. The experiments for examining the acceleration of that algorithm on the Reconfigurable DataFlow Computers (RDC) are performed with two types of mammogram images with different resolutions. There were, also, several DFE configurations and each of them gave different acceleration of algorithm execution. Those accelerations are presented and experimental results have been shown good acceleration. Also, image processing using a mean filtering algorithm combined with thresholding and binarization algorithms and 3D visualization of murine lungs using marching cubes method are explained. These algorithms are mapped on the Maxeler’s DFE to significantly increase calculation speed. Optimal algorithm calculation speed was up to 20-fold baseline calculation speed.
PB  - Springer Cham
T2  - Exploring the DataFlow Supercomputing Paradigm: Example Algorithms for Selected Applications
T2  - Part of the book series: Computer Communications and Networks (CCN)
T1  - Biomedical Images Processing Using Maxeler DataFlow Engines
SP  - 197
EP  - 227
DO  - 10.1007/978-3-030-13803-5_7
ER  - 

@inbook{
author = "Peulić, Aleksandar S. and Milanković, Ivan and Mijailović, Nikola V. and Filipović, Nenad",
year = "2019",
abstract = "Image segmentation is one of the most common procedures in medical imaging applications. It is also very important task in breast cancer detection. Breast cancer detection procedure based on mammography can be divided into several stages. The first stage is the extraction of region of interest from a breast image, after which the identification of suspicious mass regions, their classification, and comparison with the existing image database follows. It is often the case that already existing image databases have large sets of data for which processing requires a lot of time, thus the acceleration of each of the processing stages in breast cancer detection is a very important issue. Image filtering is also one of the most common and important tasks in image processing applications. It is, in most cases, preprocessing procedure for 3D visualization of an image stack. In order to achieve high-quality 3D visualization of a 2D image stack, it is of particular importance that all the images of the input stack are clear and sharp, thus their filtering should be executed carefully. There are also many algorithms for 3D visualization, so it is important to choose the right one which will execute fast enough and produce satisfied quality. In this chapter, the implementation of the already existing algorithm for region-of-interest-based image segmentation for mammogram images on High-Performance Reconfigurable DataFlow Computers (HPRDC) is proposed. As a DataFlow Engine (DFE) of such HPRDC, Maxeler’s acceleration card is used. The experiments for examining the acceleration of that algorithm on the Reconfigurable DataFlow Computers (RDC) are performed with two types of mammogram images with different resolutions. There were, also, several DFE configurations and each of them gave different acceleration of algorithm execution. Those accelerations are presented and experimental results have been shown good acceleration. Also, image processing using a mean filtering algorithm combined with thresholding and binarization algorithms and 3D visualization of murine lungs using marching cubes method are explained. These algorithms are mapped on the Maxeler’s DFE to significantly increase calculation speed. Optimal algorithm calculation speed was up to 20-fold baseline calculation speed.",
publisher = "Springer Cham",
journal = "Exploring the DataFlow Supercomputing Paradigm: Example Algorithms for Selected Applications, Part of the book series: Computer Communications and Networks (CCN)",
booktitle = "Biomedical Images Processing Using Maxeler DataFlow Engines",
pages = "197-227",
doi = "10.1007/978-3-030-13803-5_7"
}

Peulić, A. S., Milanković, I., Mijailović, N. V.,& Filipović, N.. (2019). Biomedical Images Processing Using Maxeler DataFlow Engines. in Exploring the DataFlow Supercomputing Paradigm: Example Algorithms for Selected Applications
Springer Cham., 197-227.
https://doi.org/10.1007/978-3-030-13803-5_7

Peulić AS, Milanković I, Mijailović NV, Filipović N. Biomedical Images Processing Using Maxeler DataFlow Engines. in Exploring the DataFlow Supercomputing Paradigm: Example Algorithms for Selected Applications. 2019;:197-227.
doi:10.1007/978-3-030-13803-5_7 .

Peulić, Aleksandar S., Milanković, Ivan, Mijailović, Nikola V., Filipović, Nenad, "Biomedical Images Processing Using Maxeler DataFlow Engines" in Exploring the DataFlow Supercomputing Paradigm: Example Algorithms for Selected Applications (2019):197-227,
https://doi.org/10.1007/978-3-030-13803-5_7 . .

TY  - JOUR
AU  - Milanković, Ivan L.
AU  - Mijailović, Nikola V.
AU  - Filipović, Nenad
AU  - Peulić, Aleksandar
PY  - 2017
UR  - https://gery.gef.bg.ac.rs/handle/123456789/833
AB  - Image segmentation is one of the most common procedures in medical imaging applications. It is also a very important task in breast cancer detection. Breast cancer detection procedure based on mammography can be divided into several stages. The first stage is the extraction of the region of interest from a breast image, followed by the identification of suspicious mass regions, their classification, and comparison with the existing image database. It is often the case that already existing image databases have large sets of data whose processing requires a lot of time, and thus the acceleration of each of the processing stages in breast cancer detection is a very important issue. In this paper, the implementation of the already existing algorithm for region-of-interest based image segmentation for mammogram images on High-Performance Reconfigurable Dataflow Computers (HPRDCs) is proposed. As a dataflow engine (DFE) of such HPRDC, Maxeler's acceleration card is used. The experiments for examining the acceleration of that algorithm on the Reconfigurable Dataflow Computers (RDCs) are performed with two types of mammogram images with different resolutions. There were, also, several DFE configurations and each of them gave a different acceleration value of algorithm execution. Those acceleration values are presented and experimental results showed good acceleration.
PB  - Hindawi Ltd, London
T2  - Computational and Mathematical Methods In Medicine
T1  - Acceleration of Image Segmentation Algorithm for (Breast) Mammogram Images Using High-Performance Reconfigurable Dataflow Computers
DO  - 10.1155/2017/7909282
UR  - https://hdl.handle.net/21.15107/rcub_gery_833
ER  - 

@article{
author = "Milanković, Ivan L. and Mijailović, Nikola V. and Filipović, Nenad and Peulić, Aleksandar",
year = "2017",
abstract = "Image segmentation is one of the most common procedures in medical imaging applications. It is also a very important task in breast cancer detection. Breast cancer detection procedure based on mammography can be divided into several stages. The first stage is the extraction of the region of interest from a breast image, followed by the identification of suspicious mass regions, their classification, and comparison with the existing image database. It is often the case that already existing image databases have large sets of data whose processing requires a lot of time, and thus the acceleration of each of the processing stages in breast cancer detection is a very important issue. In this paper, the implementation of the already existing algorithm for region-of-interest based image segmentation for mammogram images on High-Performance Reconfigurable Dataflow Computers (HPRDCs) is proposed. As a dataflow engine (DFE) of such HPRDC, Maxeler's acceleration card is used. The experiments for examining the acceleration of that algorithm on the Reconfigurable Dataflow Computers (RDCs) are performed with two types of mammogram images with different resolutions. There were, also, several DFE configurations and each of them gave a different acceleration value of algorithm execution. Those acceleration values are presented and experimental results showed good acceleration.",
publisher = "Hindawi Ltd, London",
journal = "Computational and Mathematical Methods In Medicine",
title = "Acceleration of Image Segmentation Algorithm for (Breast) Mammogram Images Using High-Performance Reconfigurable Dataflow Computers",
doi = "10.1155/2017/7909282",
url = "https://hdl.handle.net/21.15107/rcub_gery_833"
}

Milanković, I. L., Mijailović, N. V., Filipović, N.,& Peulić, A.. (2017). Acceleration of Image Segmentation Algorithm for (Breast) Mammogram Images Using High-Performance Reconfigurable Dataflow Computers. in Computational and Mathematical Methods In Medicine
Hindawi Ltd, London..
https://doi.org/10.1155/2017/7909282
https://hdl.handle.net/21.15107/rcub_gery_833

Milanković IL, Mijailović NV, Filipović N, Peulić A. Acceleration of Image Segmentation Algorithm for (Breast) Mammogram Images Using High-Performance Reconfigurable Dataflow Computers. in Computational and Mathematical Methods In Medicine. 2017;.
doi:10.1155/2017/7909282
https://hdl.handle.net/21.15107/rcub_gery_833 .

Milanković, Ivan L., Mijailović, Nikola V., Filipović, Nenad, Peulić, Aleksandar, "Acceleration of Image Segmentation Algorithm for (Breast) Mammogram Images Using High-Performance Reconfigurable Dataflow Computers" in Computational and Mathematical Methods In Medicine (2017),
https://doi.org/10.1155/2017/7909282 .,
https://hdl.handle.net/21.15107/rcub_gery_833 .

TY  - CONF
AU  - Peulić, Aleksandar
AU  - Milanković, Ivan L.
AU  - Mijailović, Nikola V.
AU  - Jovanović, Željko
PY  - 2016
UR  - https://gery.gef.bg.ac.rs/handle/123456789/771
AB  - The purpose of this study was to determine range of motion values of lumbar spine in rehabilitation procedure after surgery, using wearable wireless sensors. In this paper, we present a method for determining the mobility of the spinal column using a network of sensors. The sensors consist of accelerometers and gyroscopes, and mutual communication is accomplished using a I2C bus. The main sensor node collects data from all the sensors and sends them to a computer using Bluetooth communication. The collected data is then filtered and converted to the values of the angles that are of interest to quantify the movement.
PB  - IEEE, New York
C3  - Proceedings of 13th International Conference on Remote Engineering and Virtual Instrumentation
T1  - Remotely Analyze Spine Angle in Rehabilitation After Spine Surgery using Acceleration and Gyro Sensors
SP  - 281
EP  - 282
UR  - https://hdl.handle.net/21.15107/rcub_gery_771
ER  - 

@conference{
author = "Peulić, Aleksandar and Milanković, Ivan L. and Mijailović, Nikola V. and Jovanović, Željko",
year = "2016",
abstract = "The purpose of this study was to determine range of motion values of lumbar spine in rehabilitation procedure after surgery, using wearable wireless sensors. In this paper, we present a method for determining the mobility of the spinal column using a network of sensors. The sensors consist of accelerometers and gyroscopes, and mutual communication is accomplished using a I2C bus. The main sensor node collects data from all the sensors and sends them to a computer using Bluetooth communication. The collected data is then filtered and converted to the values of the angles that are of interest to quantify the movement.",
publisher = "IEEE, New York",
journal = "Proceedings of 13th International Conference on Remote Engineering and Virtual Instrumentation",
title = "Remotely Analyze Spine Angle in Rehabilitation After Spine Surgery using Acceleration and Gyro Sensors",
pages = "281-282",
url = "https://hdl.handle.net/21.15107/rcub_gery_771"
}

Peulić, A., Milanković, I. L., Mijailović, N. V.,& Jovanović, Ž.. (2016). Remotely Analyze Spine Angle in Rehabilitation After Spine Surgery using Acceleration and Gyro Sensors. in Proceedings of 13th International Conference on Remote Engineering and Virtual Instrumentation
IEEE, New York., 281-282.
https://hdl.handle.net/21.15107/rcub_gery_771

Peulić A, Milanković IL, Mijailović NV, Jovanović Ž. Remotely Analyze Spine Angle in Rehabilitation After Spine Surgery using Acceleration and Gyro Sensors. in Proceedings of 13th International Conference on Remote Engineering and Virtual Instrumentation. 2016;:281-282.
https://hdl.handle.net/21.15107/rcub_gery_771 .

Peulić, Aleksandar, Milanković, Ivan L., Mijailović, Nikola V., Jovanović, Željko, "Remotely Analyze Spine Angle in Rehabilitation After Spine Surgery using Acceleration and Gyro Sensors" in Proceedings of 13th International Conference on Remote Engineering and Virtual Instrumentation (2016):281-282,
https://hdl.handle.net/21.15107/rcub_gery_771 .

TY  - JOUR
AU  - Milanković, Ivan L.
AU  - Mijailović, Nikola V.
AU  - Peulić, Aleksandar
AU  - Nikolić, Dalibor
AU  - Končar, Igor
AU  - Exarchos, Themis
AU  - Parodi, Oberdan
AU  - Filipović, Nenad
PY  - 2015
UR  - https://gery.gef.bg.ac.rs/handle/123456789/714
AB  - The main goal of this paper is to describe two different systems that were developed for the purpose of abdominal aortic aneurysm mechanical properties investigation and to present the results of the measurements. The first system is based on the "Bubble Inflated" method and it increases the pressure of physiological saline which affects blood vessel tissue and causes mechanical deformation. The system provides recording the data about the current value of the pressure in the physiological saline by using the appropriate pressure sensor. The second system makes stretches of the vessel tissue in uni-axial direction and save the data about the force and the elongation. Both of these systems use cameras for assessment of the deformation. Obtained results from both systems are used for numerical simulation of computer model for abdominal aortic aneurysm. It gives a new avenue for application of software and hardware systems for determination of vascular tissue properties in the clinical practice.
PB  - Beograd : Univerzitet u Beogradu - Mašinski fakultet
T2  - FME Transactions
T1  - Software and Hardware Systems for Abdominal Aortic Aneurysm Mechanical Properties Investigation
VL  - 43
IS  - 2
SP  - 161
EP  - 167
DO  - 10.5937/fmet1502161M
UR  - https://hdl.handle.net/21.15107/rcub_gery_714
ER  - 

@article{
author = "Milanković, Ivan L. and Mijailović, Nikola V. and Peulić, Aleksandar and Nikolić, Dalibor and Končar, Igor and Exarchos, Themis and Parodi, Oberdan and Filipović, Nenad",
year = "2015",
abstract = "The main goal of this paper is to describe two different systems that were developed for the purpose of abdominal aortic aneurysm mechanical properties investigation and to present the results of the measurements. The first system is based on the "Bubble Inflated" method and it increases the pressure of physiological saline which affects blood vessel tissue and causes mechanical deformation. The system provides recording the data about the current value of the pressure in the physiological saline by using the appropriate pressure sensor. The second system makes stretches of the vessel tissue in uni-axial direction and save the data about the force and the elongation. Both of these systems use cameras for assessment of the deformation. Obtained results from both systems are used for numerical simulation of computer model for abdominal aortic aneurysm. It gives a new avenue for application of software and hardware systems for determination of vascular tissue properties in the clinical practice.",
publisher = "Beograd : Univerzitet u Beogradu - Mašinski fakultet",
journal = "FME Transactions",
title = "Software and Hardware Systems for Abdominal Aortic Aneurysm Mechanical Properties Investigation",
volume = "43",
number = "2",
pages = "161-167",
doi = "10.5937/fmet1502161M",
url = "https://hdl.handle.net/21.15107/rcub_gery_714"
}

Milanković, I. L., Mijailović, N. V., Peulić, A., Nikolić, D., Končar, I., Exarchos, T., Parodi, O.,& Filipović, N.. (2015). Software and Hardware Systems for Abdominal Aortic Aneurysm Mechanical Properties Investigation. in FME Transactions
Beograd : Univerzitet u Beogradu - Mašinski fakultet., 43(2), 161-167.
https://doi.org/10.5937/fmet1502161M
https://hdl.handle.net/21.15107/rcub_gery_714

Milanković IL, Mijailović NV, Peulić A, Nikolić D, Končar I, Exarchos T, Parodi O, Filipović N. Software and Hardware Systems for Abdominal Aortic Aneurysm Mechanical Properties Investigation. in FME Transactions. 2015;43(2):161-167.
doi:10.5937/fmet1502161M
https://hdl.handle.net/21.15107/rcub_gery_714 .

Milanković, Ivan L., Mijailović, Nikola V., Peulić, Aleksandar, Nikolić, Dalibor, Končar, Igor, Exarchos, Themis, Parodi, Oberdan, Filipović, Nenad, "Software and Hardware Systems for Abdominal Aortic Aneurysm Mechanical Properties Investigation" in FME Transactions, 43, no. 2 (2015):161-167,
https://doi.org/10.5937/fmet1502161M .,
https://hdl.handle.net/21.15107/rcub_gery_714 .

TY  - CONF
AU  - Mijailović, Nikola V.
AU  - Radaković, Radivoje
AU  - Peulić, Aleksandar
AU  - Milanković, Ivan L.
AU  - Filipović, Nenad
PY  - 2015
UR  - https://gery.gef.bg.ac.rs/handle/123456789/733
PB  - Institute of Electrical and Electronics Engineers Inc.
C3  - 2015 IEEE 15th International Conference on Bioinformatics and Bioengineering, BIBE 2015
T1  - Using force plate, computer simulation and image alignment in jumping analysis
DO  - 10.1109/BIBE.2015.7367672
UR  - https://hdl.handle.net/21.15107/rcub_gery_733
ER  - 

@conference{
author = "Mijailović, Nikola V. and Radaković, Radivoje and Peulić, Aleksandar and Milanković, Ivan L. and Filipović, Nenad",
year = "2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
journal = "2015 IEEE 15th International Conference on Bioinformatics and Bioengineering, BIBE 2015",
title = "Using force plate, computer simulation and image alignment in jumping analysis",
doi = "10.1109/BIBE.2015.7367672",
url = "https://hdl.handle.net/21.15107/rcub_gery_733"
}

Mijailović, N. V., Radaković, R., Peulić, A., Milanković, I. L.,& Filipović, N.. (2015). Using force plate, computer simulation and image alignment in jumping analysis. in 2015 IEEE 15th International Conference on Bioinformatics and Bioengineering, BIBE 2015
Institute of Electrical and Electronics Engineers Inc...
https://doi.org/10.1109/BIBE.2015.7367672
https://hdl.handle.net/21.15107/rcub_gery_733

Mijailović NV, Radaković R, Peulić A, Milanković IL, Filipović N. Using force plate, computer simulation and image alignment in jumping analysis. in 2015 IEEE 15th International Conference on Bioinformatics and Bioengineering, BIBE 2015. 2015;.
doi:10.1109/BIBE.2015.7367672
https://hdl.handle.net/21.15107/rcub_gery_733 .

Mijailović, Nikola V., Radaković, Radivoje, Peulić, Aleksandar, Milanković, Ivan L., Filipović, Nenad, "Using force plate, computer simulation and image alignment in jumping analysis" in 2015 IEEE 15th International Conference on Bioinformatics and Bioengineering, BIBE 2015 (2015),
https://doi.org/10.1109/BIBE.2015.7367672 .,
https://hdl.handle.net/21.15107/rcub_gery_733 .

TY  - CONF
AU  - Milanković, Ivan L.
AU  - Peulić, Aleksandar
AU  - Ysasi, A.B.
AU  - Wagner, W.L.
AU  - Pabst, A.M.
AU  - Ackermann, M.
AU  - Houdek, J.
AU  - Föhst, S.
AU  - Mentzer, S.J.
AU  - Konerding, M.A.
AU  - Filipović, Nenad
AU  - Tsuda, A.
PY  - 2015
UR  - https://gery.gef.bg.ac.rs/handle/123456789/732
AB  - Image filtering is one of the most common and important tasks in image processing applications. In this paper, image processing using a mean filtering algorithm combined with thresholding and binarization algorithms for the 3D visualization and analysis of murine lungs is explained. These algorithms are then mapped on the Maxler's MAX2336B Dataflow Engine (DFE) to significantly increase calculation speed. Several different DFE configurations were tested and each yielded different performance characteristics. Optimal algorithm calculation speed was up to 30 fold baseline calculation speed.
PB  - Institute of Electrical and Electronics Engineers Inc.
C3  - 2015 IEEE 15th International Conference on Bioinformatics and Bioengineering, BIBE 2015
T1  - Acceleration of image filtering algorithms for 3D visualization of murine lungs using dataflow engines
DO  - 10.1109/BIBE.2015.7367663
UR  - https://hdl.handle.net/21.15107/rcub_gery_732
ER  - 

@conference{
author = "Milanković, Ivan L. and Peulić, Aleksandar and Ysasi, A.B. and Wagner, W.L. and Pabst, A.M. and Ackermann, M. and Houdek, J. and Föhst, S. and Mentzer, S.J. and Konerding, M.A. and Filipović, Nenad and Tsuda, A.",
year = "2015",
abstract = "Image filtering is one of the most common and important tasks in image processing applications. In this paper, image processing using a mean filtering algorithm combined with thresholding and binarization algorithms for the 3D visualization and analysis of murine lungs is explained. These algorithms are then mapped on the Maxler's MAX2336B Dataflow Engine (DFE) to significantly increase calculation speed. Several different DFE configurations were tested and each yielded different performance characteristics. Optimal algorithm calculation speed was up to 30 fold baseline calculation speed.",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
journal = "2015 IEEE 15th International Conference on Bioinformatics and Bioengineering, BIBE 2015",
title = "Acceleration of image filtering algorithms for 3D visualization of murine lungs using dataflow engines",
doi = "10.1109/BIBE.2015.7367663",
url = "https://hdl.handle.net/21.15107/rcub_gery_732"
}

Milanković, I. L., Peulić, A., Ysasi, A.B., Wagner, W.L., Pabst, A.M., Ackermann, M., Houdek, J., Föhst, S., Mentzer, S.J., Konerding, M.A., Filipović, N.,& Tsuda, A.. (2015). Acceleration of image filtering algorithms for 3D visualization of murine lungs using dataflow engines. in 2015 IEEE 15th International Conference on Bioinformatics and Bioengineering, BIBE 2015
Institute of Electrical and Electronics Engineers Inc...
https://doi.org/10.1109/BIBE.2015.7367663
https://hdl.handle.net/21.15107/rcub_gery_732

Milanković IL, Peulić A, Ysasi A, Wagner W, Pabst A, Ackermann M, Houdek J, Föhst S, Mentzer S, Konerding M, Filipović N, Tsuda A. Acceleration of image filtering algorithms for 3D visualization of murine lungs using dataflow engines. in 2015 IEEE 15th International Conference on Bioinformatics and Bioengineering, BIBE 2015. 2015;.
doi:10.1109/BIBE.2015.7367663
https://hdl.handle.net/21.15107/rcub_gery_732 .

Milanković, Ivan L., Peulić, Aleksandar, Ysasi, A.B., Wagner, W.L., Pabst, A.M., Ackermann, M., Houdek, J., Föhst, S., Mentzer, S.J., Konerding, M.A., Filipović, Nenad, Tsuda, A., "Acceleration of image filtering algorithms for 3D visualization of murine lungs using dataflow engines" in 2015 IEEE 15th International Conference on Bioinformatics and Bioengineering, BIBE 2015 (2015),
https://doi.org/10.1109/BIBE.2015.7367663 .,
https://hdl.handle.net/21.15107/rcub_gery_732 .

TY  - JOUR
AU  - Milovanović, A.M.
AU  - Koprivica, B.M.
AU  - Peulić, Aleksandar
AU  - Milanković, Ivan L.
PY  - 2015
UR  - https://gery.gef.bg.ac.rs/handle/123456789/723
AB  - In this paper, the Equivalent Electrodes Method (EEM) has been proposed for the analysis of square coaxial lines family. Lines with single and two layer perfect or imperfect medium have been analyzed. The capacitance per unit length of these lines has been calculated. The results obtained by EEM have been compared with those reported in the literature, obtained by other methods, and those obtained by using software package COMSOL Multiphysics. Also, with the aim of comparison of the results, capacitance measurements based on a high resolution CDC (Capacitance to Digital Converter) have been realized. All results obtained have been found to be in very good agreement.
PB  - Applied Computational Electromagnetics Society (ACES)
T2  - Applied Computational Electromagnetics Society Journal
T1  - Analysis of Square Coaxial Line Family
VL  - 30
IS  - 1
SP  - 99
EP  - 108
UR  - https://hdl.handle.net/21.15107/rcub_gery_723
ER  - 

@article{
author = "Milovanović, A.M. and Koprivica, B.M. and Peulić, Aleksandar and Milanković, Ivan L.",
year = "2015",
abstract = "In this paper, the Equivalent Electrodes Method (EEM) has been proposed for the analysis of square coaxial lines family. Lines with single and two layer perfect or imperfect medium have been analyzed. The capacitance per unit length of these lines has been calculated. The results obtained by EEM have been compared with those reported in the literature, obtained by other methods, and those obtained by using software package COMSOL Multiphysics. Also, with the aim of comparison of the results, capacitance measurements based on a high resolution CDC (Capacitance to Digital Converter) have been realized. All results obtained have been found to be in very good agreement.",
publisher = "Applied Computational Electromagnetics Society (ACES)",
journal = "Applied Computational Electromagnetics Society Journal",
title = "Analysis of Square Coaxial Line Family",
volume = "30",
number = "1",
pages = "99-108",
url = "https://hdl.handle.net/21.15107/rcub_gery_723"
}

Milovanović, A.M., Koprivica, B.M., Peulić, A.,& Milanković, I. L.. (2015). Analysis of Square Coaxial Line Family. in Applied Computational Electromagnetics Society Journal
Applied Computational Electromagnetics Society (ACES)., 30(1), 99-108.
https://hdl.handle.net/21.15107/rcub_gery_723

Milovanović A, Koprivica B, Peulić A, Milanković IL. Analysis of Square Coaxial Line Family. in Applied Computational Electromagnetics Society Journal. 2015;30(1):99-108.
https://hdl.handle.net/21.15107/rcub_gery_723 .

Milovanović, A.M., Koprivica, B.M., Peulić, Aleksandar, Milanković, Ivan L., "Analysis of Square Coaxial Line Family" in Applied Computational Electromagnetics Society Journal, 30, no. 1 (2015):99-108,
https://hdl.handle.net/21.15107/rcub_gery_723 .

TY  - JOUR
AU  - Mijailović, Nikola V.
AU  - Vulović, Radun
AU  - Milanković, Ivan L.
AU  - Radaković, Radivoje
AU  - Filipović, Nenad
AU  - Peulić, Aleksandar
PY  - 2015
UR  - https://gery.gef.bg.ac.rs/handle/123456789/712
AB  - Knowledge about the knee cartilage deformation ratio as well as the knee cartilage stress distribution is of particular importance in clinical studies due to the fact that these represent some of the basic indicators of cartilage state and that they also provide information about joint cartilage wear so medical doctors can predict when it is necessary to perform surgery on a patient. In this research, we apply various kinds of sensors such as a system of infrared cameras and reflective markers, three-axis accelerometer, and force plate. The fluorescent marker and accelerometers are placed on the patient's hip, knee, and ankle, respectively. During a normal walk we are recording the space position of markers, acceleration, and ground reaction force by force plate. Measured data are included in the biomechanical model of the knee joint. Geometry for this model is defined from CT images. This model includes the impact of ground reaction forces, contact force between femur and tibia, patient body weight, ligaments, and muscle forces. The boundary conditions are created for the finite element method in order to noninvasively determine the cartilage stress distribution.
PB  - Hindawi Publishing Corp, New York
T2  - Computational and Mathematical Methods In Medicine
T1  - Assessment of Knee Cartilage Stress Distribution and Deformation Using Motion Capture System and Wearable Sensors for Force Ratio Detection
DO  - 10.1155/2015/963746
UR  - https://hdl.handle.net/21.15107/rcub_gery_712
ER  - 

@article{
author = "Mijailović, Nikola V. and Vulović, Radun and Milanković, Ivan L. and Radaković, Radivoje and Filipović, Nenad and Peulić, Aleksandar",
year = "2015",
abstract = "Knowledge about the knee cartilage deformation ratio as well as the knee cartilage stress distribution is of particular importance in clinical studies due to the fact that these represent some of the basic indicators of cartilage state and that they also provide information about joint cartilage wear so medical doctors can predict when it is necessary to perform surgery on a patient. In this research, we apply various kinds of sensors such as a system of infrared cameras and reflective markers, three-axis accelerometer, and force plate. The fluorescent marker and accelerometers are placed on the patient's hip, knee, and ankle, respectively. During a normal walk we are recording the space position of markers, acceleration, and ground reaction force by force plate. Measured data are included in the biomechanical model of the knee joint. Geometry for this model is defined from CT images. This model includes the impact of ground reaction forces, contact force between femur and tibia, patient body weight, ligaments, and muscle forces. The boundary conditions are created for the finite element method in order to noninvasively determine the cartilage stress distribution.",
publisher = "Hindawi Publishing Corp, New York",
journal = "Computational and Mathematical Methods In Medicine",
title = "Assessment of Knee Cartilage Stress Distribution and Deformation Using Motion Capture System and Wearable Sensors for Force Ratio Detection",
doi = "10.1155/2015/963746",
url = "https://hdl.handle.net/21.15107/rcub_gery_712"
}

Mijailović, N. V., Vulović, R., Milanković, I. L., Radaković, R., Filipović, N.,& Peulić, A.. (2015). Assessment of Knee Cartilage Stress Distribution and Deformation Using Motion Capture System and Wearable Sensors for Force Ratio Detection. in Computational and Mathematical Methods In Medicine
Hindawi Publishing Corp, New York..
https://doi.org/10.1155/2015/963746
https://hdl.handle.net/21.15107/rcub_gery_712

Mijailović NV, Vulović R, Milanković IL, Radaković R, Filipović N, Peulić A. Assessment of Knee Cartilage Stress Distribution and Deformation Using Motion Capture System and Wearable Sensors for Force Ratio Detection. in Computational and Mathematical Methods In Medicine. 2015;.
doi:10.1155/2015/963746
https://hdl.handle.net/21.15107/rcub_gery_712 .

Mijailović, Nikola V., Vulović, Radun, Milanković, Ivan L., Radaković, Radivoje, Filipović, Nenad, Peulić, Aleksandar, "Assessment of Knee Cartilage Stress Distribution and Deformation Using Motion Capture System and Wearable Sensors for Force Ratio Detection" in Computational and Mathematical Methods In Medicine (2015),
https://doi.org/10.1155/2015/963746 .,
https://hdl.handle.net/21.15107/rcub_gery_712 .