The Experts below are selected from a list of 5364 Experts worldwide ranked by ideXlab platform

Alexander Bryekhov - One of the best experts on this subject based on the ideXlab platform.

  • Modeling stress–strain state of screw transpedicular spine fixation system with variable structure of the Vertebral Body
    Journal of Biomechanics, 2011
    Co-Authors: Oleksiy Kovalenko, Mykhaylo Kalinin, Alexander Polyakov, Alexander Bryekhov
    Abstract:

    To ensure the stability of the spine in the postoperative period transpedicular fixation spine's elements is often used. Usually transpedicular system is formed from the rods that eventually form the frame structure type, attached with screws to the Vertebrae. Such design must be rigid and take active part spine loads without significant deformation. Simple transpedicular system can be represented as: bone-1–transpedicular screw-1–Bar–transpedicular screw-2–bell-2–Cage–bell-1. This bar takes in about 20% and Cage takes in about 80% applied load. From the standpoint of improving the well-known structures interest should be given in their stress–strain state as a whole, and for each of the elements, in particular. This study was held in modeling of pedicle screw and the estimation of its deformation, taking into account the interaction with the Body of Vertebra, which has a variable structure. Vertebra has a complex structure provided with hard enough outer (cortical) layer and soft inner Body. A simplified model can be considered with homogeneous materials characterized by different Young's modulus and Poisson's ratio. Transpedicular screw can be represented as a bar having a variable cross-section, located on an elastic base, characterized by different modulus of subgrade reaction. The modulus of subgrade reaction of the elastic foundation is changing stepwise at the transition from one layer of the Vertebral Body to another. In addition, it is assumed that the Vertebra is rigidly clamped (conditionally stationary), and the load is transferred from the screw rod, being uniformly distributed along the length of the local section at the end of the screw. The numerical solution of this problem was obtained by using the generalized Heaviside function. Analysis of the solution indicates that the greatest strain occurs in the area of the screw located in the cortical layer of the Vertebra, while the rest is practically not deformed. The same problem was solved by the finite element method in the medium CosmosDesignStar. At the same time 3D-models were used for the spinal segment, fixed transpedicular system. Results of solutions obtained by the two methods described above were sufficiently close, suggesting the adequacy of the proposed model with respect to the real conditions. Thus, the proposed technique can be used to analyze the stress–strain state of various screws, to assess the impact of new constructional elements of screws on the nature of their deformations, to develop improved designs of transpedicular systems, including their dynamics.

Noriyuki Moriyama - One of the best experts on this subject based on the ideXlab platform.

  • Medical Imaging: Image Processing - CAD system for coronary calcifications based on helical CT images
    Medical Imaging 1999: Image Processing, 1999
    Co-Authors: Yuji Ukai, Noboru Niki, Hitoshi Satoh, S. Watanabe, Hironobu Ohmatsu, Kenji Eguchi, Noriyuki Moriyama
    Abstract:

    In this paper, we describe a computer assisted diagnosis algorithm of coronary calcifications based on helical X-ray CT images which are used at the mass screening process for lung cancer diagnosis. Our diagnostic algorithm consists of four processes: Firstly, we choose the heart slices from the CT images which was taken from the mass screening, we classify the heart slices to three section. Second, we extract the heart region on each slice by the shape of the lung area and the Body of Vertebra. Third, the candidate regions of the coronary calcifications are detected by the difference calculus and thresholding process. Finally, to increase the effectiveness of the diagnostic processing, we cancel the artifacts included in the candidate regions by the diagnostic rules defined by us. We show here the result of our algorithm which is applied to helical CT images of 462 patients analyzed for lung cancer screening.

  • Medical Imaging: Image Processing - Coronary calcification diagnosis system based on helical CT images
    Medical Imaging 1998: Image Processing, 1998
    Co-Authors: Yuji Ukai, Noboru Niki, Hitoshi Satoh, S. Watanabe, Hironobu Ohmatsu, Kenji Eguchi, Noriyuki Moriyama
    Abstract:

    In this paper, we describe a computer assisted diagnosis algorithm of coronary calcifications based on helical X-ray CT images which are used at the mass screening process for lung cancer diagnosis. Our diagnostic algorithm consists of four processes: Firstly, we choose the heart slices from the CT images which was taken from the mass screening, we classify the heart slices to three section. Second, we extract the heart region on each slice by the shape of the lung area and the Body of Vertebra. Third, the candidate regions of the coronary calcifications are detected by the difference calculus and thresholding process. Finally, to increase the effectiveness of the diagnostic processing, we cancel the artifacts included in the candidate regions by the diagnostic rules defined by us. We show here the result of our algorithm which is applied to helical CT images of 402 patients analyzed for lung cancer screening.

  • A coronary calcification diagnosis system based on helical CT images
    IEEE Transactions on Nuclear Science, 1998
    Co-Authors: Yuji Ukai, Noboru Niki, Hitoshi Satoh, S. Watanabe, Hironobu Ohmatsu, Kenji Eguchi, Noriyuki Moriyama
    Abstract:

    Describes a computer assisted diagnostic algorithm for coronary calcifications based on helical X-ray CT images which is used in mass screening process for lung cancer diagnosis. The authors' diagnostic algorithm consists of four processes: First, they choose the heart slices from the CT images which were taken at the mass screening. They classify the heart slices into three sections which have different coronary geometries, using the information of the heart shape, trachea, CT values in the heart region, and the bone. Second, the authors extract the heart region in each slice, using the information of the lung shape and the Body of Vertebra. Third, they detect the candidate regions of the coronary calcifications using an edge filter and thresholding pixel values. Finally, to increase the effectiveness of the diagnosis, the authors exclude the artifact regions included in the candidate regions by using the diagnostic rule based on a neural network. They applied this algorithm to helical CT images of 462 patients screened for lung cancer. The results generated by this system were compared with a physician's diagnosis. This system could detect 213 of 214 regions which were diagnosed as coronary calcifications or probably coronary calcifications by a physician. There was only one false negative case. The false positive ratio was 0.30 per patient.

Oleksiy Kovalenko - One of the best experts on this subject based on the ideXlab platform.

  • Modeling stress–strain state of screw transpedicular spine fixation system with variable structure of the Vertebral Body
    Journal of Biomechanics, 2011
    Co-Authors: Oleksiy Kovalenko, Mykhaylo Kalinin, Alexander Polyakov, Alexander Bryekhov
    Abstract:

    To ensure the stability of the spine in the postoperative period transpedicular fixation spine's elements is often used. Usually transpedicular system is formed from the rods that eventually form the frame structure type, attached with screws to the Vertebrae. Such design must be rigid and take active part spine loads without significant deformation. Simple transpedicular system can be represented as: bone-1–transpedicular screw-1–Bar–transpedicular screw-2–bell-2–Cage–bell-1. This bar takes in about 20% and Cage takes in about 80% applied load. From the standpoint of improving the well-known structures interest should be given in their stress–strain state as a whole, and for each of the elements, in particular. This study was held in modeling of pedicle screw and the estimation of its deformation, taking into account the interaction with the Body of Vertebra, which has a variable structure. Vertebra has a complex structure provided with hard enough outer (cortical) layer and soft inner Body. A simplified model can be considered with homogeneous materials characterized by different Young's modulus and Poisson's ratio. Transpedicular screw can be represented as a bar having a variable cross-section, located on an elastic base, characterized by different modulus of subgrade reaction. The modulus of subgrade reaction of the elastic foundation is changing stepwise at the transition from one layer of the Vertebral Body to another. In addition, it is assumed that the Vertebra is rigidly clamped (conditionally stationary), and the load is transferred from the screw rod, being uniformly distributed along the length of the local section at the end of the screw. The numerical solution of this problem was obtained by using the generalized Heaviside function. Analysis of the solution indicates that the greatest strain occurs in the area of the screw located in the cortical layer of the Vertebra, while the rest is practically not deformed. The same problem was solved by the finite element method in the medium CosmosDesignStar. At the same time 3D-models were used for the spinal segment, fixed transpedicular system. Results of solutions obtained by the two methods described above were sufficiently close, suggesting the adequacy of the proposed model with respect to the real conditions. Thus, the proposed technique can be used to analyze the stress–strain state of various screws, to assess the impact of new constructional elements of screws on the nature of their deformations, to develop improved designs of transpedicular systems, including their dynamics.

Yuji Ukai - One of the best experts on this subject based on the ideXlab platform.

  • Medical Imaging: Image Processing - CAD system for coronary calcifications based on helical CT images
    Medical Imaging 1999: Image Processing, 1999
    Co-Authors: Yuji Ukai, Noboru Niki, Hitoshi Satoh, S. Watanabe, Hironobu Ohmatsu, Kenji Eguchi, Noriyuki Moriyama
    Abstract:

    In this paper, we describe a computer assisted diagnosis algorithm of coronary calcifications based on helical X-ray CT images which are used at the mass screening process for lung cancer diagnosis. Our diagnostic algorithm consists of four processes: Firstly, we choose the heart slices from the CT images which was taken from the mass screening, we classify the heart slices to three section. Second, we extract the heart region on each slice by the shape of the lung area and the Body of Vertebra. Third, the candidate regions of the coronary calcifications are detected by the difference calculus and thresholding process. Finally, to increase the effectiveness of the diagnostic processing, we cancel the artifacts included in the candidate regions by the diagnostic rules defined by us. We show here the result of our algorithm which is applied to helical CT images of 462 patients analyzed for lung cancer screening.

  • Medical Imaging: Image Processing - Coronary calcification diagnosis system based on helical CT images
    Medical Imaging 1998: Image Processing, 1998
    Co-Authors: Yuji Ukai, Noboru Niki, Hitoshi Satoh, S. Watanabe, Hironobu Ohmatsu, Kenji Eguchi, Noriyuki Moriyama
    Abstract:

    In this paper, we describe a computer assisted diagnosis algorithm of coronary calcifications based on helical X-ray CT images which are used at the mass screening process for lung cancer diagnosis. Our diagnostic algorithm consists of four processes: Firstly, we choose the heart slices from the CT images which was taken from the mass screening, we classify the heart slices to three section. Second, we extract the heart region on each slice by the shape of the lung area and the Body of Vertebra. Third, the candidate regions of the coronary calcifications are detected by the difference calculus and thresholding process. Finally, to increase the effectiveness of the diagnostic processing, we cancel the artifacts included in the candidate regions by the diagnostic rules defined by us. We show here the result of our algorithm which is applied to helical CT images of 402 patients analyzed for lung cancer screening.

  • A coronary calcification diagnosis system based on helical CT images
    IEEE Transactions on Nuclear Science, 1998
    Co-Authors: Yuji Ukai, Noboru Niki, Hitoshi Satoh, S. Watanabe, Hironobu Ohmatsu, Kenji Eguchi, Noriyuki Moriyama
    Abstract:

    Describes a computer assisted diagnostic algorithm for coronary calcifications based on helical X-ray CT images which is used in mass screening process for lung cancer diagnosis. The authors' diagnostic algorithm consists of four processes: First, they choose the heart slices from the CT images which were taken at the mass screening. They classify the heart slices into three sections which have different coronary geometries, using the information of the heart shape, trachea, CT values in the heart region, and the bone. Second, the authors extract the heart region in each slice, using the information of the lung shape and the Body of Vertebra. Third, they detect the candidate regions of the coronary calcifications using an edge filter and thresholding pixel values. Finally, to increase the effectiveness of the diagnosis, the authors exclude the artifact regions included in the candidate regions by using the diagnostic rule based on a neural network. They applied this algorithm to helical CT images of 462 patients screened for lung cancer. The results generated by this system were compared with a physician's diagnosis. This system could detect 213 of 214 regions which were diagnosed as coronary calcifications or probably coronary calcifications by a physician. There was only one false negative case. The false positive ratio was 0.30 per patient.

  • ICPR - An algorithm for coronary calcification diagnosis based on helical CT images
    Proceedings of 13th International Conference on Pattern Recognition, 1996
    Co-Authors: Yuji Ukai, Noboru Niki, Hitoshi Satoh, S. Watanabe, Hironobu Ohmatsu, Kenji Eguchi
    Abstract:

    We describe a computer assisted diagnosis algorithm of coronary calcifications based on helical X-ray CT images which are used at the mass screening process for lung cancer diagnosis. Our diagnostic algorithm consists of three processes: 1) we choose the CT slices including the heart region by recognition of the heart shape and the diaphragm, and we extract the heart region on each slice by the shape of the lung area and the Body of Vertebra; 2) the candidate regions of the coronary calcifications are detected by the difference calculus and thresholding process; and 3) to increase the effectiveness of the diagnostic processing, we cancel the artifacts included in the candidate regions by the diagnostic rules defined by us. We show here the result of our algorithm which is applied to helical CT images of 461 patients analyzed for lung cancer screening.

Kenji Eguchi - One of the best experts on this subject based on the ideXlab platform.

  • Medical Imaging: Image Processing - CAD system for coronary calcifications based on helical CT images
    Medical Imaging 1999: Image Processing, 1999
    Co-Authors: Yuji Ukai, Noboru Niki, Hitoshi Satoh, S. Watanabe, Hironobu Ohmatsu, Kenji Eguchi, Noriyuki Moriyama
    Abstract:

    In this paper, we describe a computer assisted diagnosis algorithm of coronary calcifications based on helical X-ray CT images which are used at the mass screening process for lung cancer diagnosis. Our diagnostic algorithm consists of four processes: Firstly, we choose the heart slices from the CT images which was taken from the mass screening, we classify the heart slices to three section. Second, we extract the heart region on each slice by the shape of the lung area and the Body of Vertebra. Third, the candidate regions of the coronary calcifications are detected by the difference calculus and thresholding process. Finally, to increase the effectiveness of the diagnostic processing, we cancel the artifacts included in the candidate regions by the diagnostic rules defined by us. We show here the result of our algorithm which is applied to helical CT images of 462 patients analyzed for lung cancer screening.

  • Medical Imaging: Image Processing - Coronary calcification diagnosis system based on helical CT images
    Medical Imaging 1998: Image Processing, 1998
    Co-Authors: Yuji Ukai, Noboru Niki, Hitoshi Satoh, S. Watanabe, Hironobu Ohmatsu, Kenji Eguchi, Noriyuki Moriyama
    Abstract:

    In this paper, we describe a computer assisted diagnosis algorithm of coronary calcifications based on helical X-ray CT images which are used at the mass screening process for lung cancer diagnosis. Our diagnostic algorithm consists of four processes: Firstly, we choose the heart slices from the CT images which was taken from the mass screening, we classify the heart slices to three section. Second, we extract the heart region on each slice by the shape of the lung area and the Body of Vertebra. Third, the candidate regions of the coronary calcifications are detected by the difference calculus and thresholding process. Finally, to increase the effectiveness of the diagnostic processing, we cancel the artifacts included in the candidate regions by the diagnostic rules defined by us. We show here the result of our algorithm which is applied to helical CT images of 402 patients analyzed for lung cancer screening.

  • A coronary calcification diagnosis system based on helical CT images
    IEEE Transactions on Nuclear Science, 1998
    Co-Authors: Yuji Ukai, Noboru Niki, Hitoshi Satoh, S. Watanabe, Hironobu Ohmatsu, Kenji Eguchi, Noriyuki Moriyama
    Abstract:

    Describes a computer assisted diagnostic algorithm for coronary calcifications based on helical X-ray CT images which is used in mass screening process for lung cancer diagnosis. The authors' diagnostic algorithm consists of four processes: First, they choose the heart slices from the CT images which were taken at the mass screening. They classify the heart slices into three sections which have different coronary geometries, using the information of the heart shape, trachea, CT values in the heart region, and the bone. Second, the authors extract the heart region in each slice, using the information of the lung shape and the Body of Vertebra. Third, they detect the candidate regions of the coronary calcifications using an edge filter and thresholding pixel values. Finally, to increase the effectiveness of the diagnosis, the authors exclude the artifact regions included in the candidate regions by using the diagnostic rule based on a neural network. They applied this algorithm to helical CT images of 462 patients screened for lung cancer. The results generated by this system were compared with a physician's diagnosis. This system could detect 213 of 214 regions which were diagnosed as coronary calcifications or probably coronary calcifications by a physician. There was only one false negative case. The false positive ratio was 0.30 per patient.

  • ICPR - An algorithm for coronary calcification diagnosis based on helical CT images
    Proceedings of 13th International Conference on Pattern Recognition, 1996
    Co-Authors: Yuji Ukai, Noboru Niki, Hitoshi Satoh, S. Watanabe, Hironobu Ohmatsu, Kenji Eguchi
    Abstract:

    We describe a computer assisted diagnosis algorithm of coronary calcifications based on helical X-ray CT images which are used at the mass screening process for lung cancer diagnosis. Our diagnostic algorithm consists of three processes: 1) we choose the CT slices including the heart region by recognition of the heart shape and the diaphragm, and we extract the heart region on each slice by the shape of the lung area and the Body of Vertebra; 2) the candidate regions of the coronary calcifications are detected by the difference calculus and thresholding process; and 3) to increase the effectiveness of the diagnostic processing, we cancel the artifacts included in the candidate regions by the diagnostic rules defined by us. We show here the result of our algorithm which is applied to helical CT images of 461 patients analyzed for lung cancer screening.