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Corrado Priami - One of the best experts on this subject based on the ideXlab platform.

  • discrete event systems specification in systems biology a discussion of stochastic pi calculus and devs
    Winter Simulation Conference, 2005
    Co-Authors: Adelinde M Uhrmacher, Corrado Priami
    Abstract:

    The goal of Systems Biology is to analyze the behavior and interrelationships between entities of entire functional biological systems. Discrete event approaches are of particular interest if small numbers of entities, like DNA molecules, shall be modeled. Two general approaches toward discrete event modeling and simulation are presented. They provide rather different perspectives on the system to be modeled, as is illustrated based on a model of the Trypophan Operon. Whereas in Devs distinctions are emphasized, e.g. between system and its environment, between structural and non structural changes, between properties attributed to a system and the system itself, these distinctions become fluent in the compact description of the π-Calculus. However, both share the problem that in order to support a comfortable modeling, adaptations and extensions according to the concrete requirements of this Challenging Application area are needed.

Adelinde M Uhrmacher - One of the best experts on this subject based on the ideXlab platform.

  • ABSTRACT DISCRETE EVENT SYSTEMS SPECIFICATION IN SYSTEMS BIOLOGY- A DISCUSSION OF STOCHASTIC PI CALCULUS AND DEVS
    2008
    Co-Authors: M. E. Kuhl, Adelinde M Uhrmacher, N. M. Steiger, F. B. Armstrong, J. A. Joines, Albert Einstein Str
    Abstract:

    The goal of Systems Biology is to analyze the behavior and interrelationships between entities of entire functional biological systems. Discrete event approaches are of particular interest if small numbers of entities, like DNA molecules, shall be modeled. Two general approaches toward discrete event modeling and simulation are presented. They provide rather different perspectives on the system to be modeled, as is illustrated based on a model of the Trypophan Operon. Whereas in Devs distinctions are emphasized, e.g. between system and its environment, between structural and non structural changes, between properties attributed to a system and the system itself, these distinctions become fluent in the compact description of the π-Calculus. However, both share the problem that in order to support a comfortable modeling, adaptations and extensions according to the concrete requirements of this Challenging Application area are needed.

  • discrete event systems specification in systems biology a discussion of stochastic pi calculus and devs
    Winter Simulation Conference, 2005
    Co-Authors: Adelinde M Uhrmacher, Corrado Priami
    Abstract:

    The goal of Systems Biology is to analyze the behavior and interrelationships between entities of entire functional biological systems. Discrete event approaches are of particular interest if small numbers of entities, like DNA molecules, shall be modeled. Two general approaches toward discrete event modeling and simulation are presented. They provide rather different perspectives on the system to be modeled, as is illustrated based on a model of the Trypophan Operon. Whereas in Devs distinctions are emphasized, e.g. between system and its environment, between structural and non structural changes, between properties attributed to a system and the system itself, these distinctions become fluent in the compact description of the π-Calculus. However, both share the problem that in order to support a comfortable modeling, adaptations and extensions according to the concrete requirements of this Challenging Application area are needed.

Peder E Z Larson - One of the best experts on this subject based on the ideXlab platform.

  • iterative motion compensation reconstruction ultra short te imoco ute for high resolution free breathing pulmonary mri
    arXiv: Image and Video Processing, 2020
    Co-Authors: Xucheng Zhu, Marilynn Chan, Michael Lustig, Kevin M Johnson, Peder E Z Larson
    Abstract:

    Purpose, To develop a high scanning efficiency, motion corrected imaging strategy for free-breathing pulmonary MRI by combining a motion compensation reconstruction with a UTE acquisition, called iMoCo UTE. Methods, An optimized golden angle ordering radial UTE sequence was used to continuously acquire data for 5 minutes. All readouts were grouped to different respiratory motion states based on self-navigator signals, then motion resolved data was reconstructed by XD Golden angle RAdial Sparse Parallel reconstruction (XD GRASP). One state from the motion resolved images was selected as a reference, and motion fields from the other states to the reference were derived via non-rigid registration. Finally, all motion resolved data and motion fields were reconstructed by using an iterative motion compensation reconstruction with a total generalized variation sparse constraint. Results, The iMoCo UTE strategy was evaluated in volunteers and non-sedated pediatric patient(4-6 y/o) studies. Images reconstructed with iMoCo UTE provided sharper anatomical lung structures, and higher apparent SNR and CNR, compared to using other motion correction strategies, such as soft-gating, motion resolved reconstruction, and non-rigid motion compensation(MoCo). iMoCo UTE also showed promising results in an infant study. Conclusions, The proposed iMoCo UTE combines self-navigation, motion modeling, and a compressed sensing reconstruction to increase scan efficiency, SNR, and reduce respiratory motion in lung MRI. This proposed strategy shows improvements in free breathing lung MRI scans, especially in very Challenging Application situations, such as pediatric MRI studies.

Larson Peder - One of the best experts on this subject based on the ideXlab platform.

  • Iterative Motion Compensation reconstruction ultra-short TE(iMoCo UTE) for high resolution free breathing pulmonary MRI
    'Wiley', 2020
    Co-Authors: Zhu Xucheng, Chan Marilynn, Lustig Michael, Johnson Kevin, Larson Peder
    Abstract:

    Purpose, To develop a high scanning efficiency, motion corrected imaging strategy for free-breathing pulmonary MRI by combining a motion compensation reconstruction with a UTE acquisition, called iMoCo UTE. Methods, An optimized golden angle ordering radial UTE sequence was used to continuously acquire data for 5 minutes. All readouts were grouped to different respiratory motion states based on self-navigator signals, then motion resolved data was reconstructed by XD Golden angle RAdial Sparse Parallel reconstruction (XD GRASP). One state from the motion resolved images was selected as a reference, and motion fields from the other states to the reference were derived via non-rigid registration. Finally, all motion resolved data and motion fields were reconstructed by using an iterative motion compensation reconstruction with a total generalized variation sparse constraint. Results, The iMoCo UTE strategy was evaluated in volunteers and non-sedated pediatric patient(4-6 y/o) studies. Images reconstructed with iMoCo UTE provided sharper anatomical lung structures, and higher apparent SNR and CNR, compared to using other motion correction strategies, such as soft-gating, motion resolved reconstruction, and non-rigid motion compensation(MoCo). iMoCo UTE also showed promising results in an infant study. Conclusions, The proposed iMoCo UTE combines self-navigation, motion modeling, and a compressed sensing reconstruction to increase scan efficiency, SNR, and reduce respiratory motion in lung MRI. This proposed strategy shows improvements in free breathing lung MRI scans, especially in very Challenging Application situations, such as pediatric MRI studies

Michael Lustig - One of the best experts on this subject based on the ideXlab platform.

  • iterative motion compensation reconstruction ultra short te imoco ute for high resolution free breathing pulmonary mri
    arXiv: Image and Video Processing, 2020
    Co-Authors: Xucheng Zhu, Marilynn Chan, Michael Lustig, Kevin M Johnson, Peder E Z Larson
    Abstract:

    Purpose, To develop a high scanning efficiency, motion corrected imaging strategy for free-breathing pulmonary MRI by combining a motion compensation reconstruction with a UTE acquisition, called iMoCo UTE. Methods, An optimized golden angle ordering radial UTE sequence was used to continuously acquire data for 5 minutes. All readouts were grouped to different respiratory motion states based on self-navigator signals, then motion resolved data was reconstructed by XD Golden angle RAdial Sparse Parallel reconstruction (XD GRASP). One state from the motion resolved images was selected as a reference, and motion fields from the other states to the reference were derived via non-rigid registration. Finally, all motion resolved data and motion fields were reconstructed by using an iterative motion compensation reconstruction with a total generalized variation sparse constraint. Results, The iMoCo UTE strategy was evaluated in volunteers and non-sedated pediatric patient(4-6 y/o) studies. Images reconstructed with iMoCo UTE provided sharper anatomical lung structures, and higher apparent SNR and CNR, compared to using other motion correction strategies, such as soft-gating, motion resolved reconstruction, and non-rigid motion compensation(MoCo). iMoCo UTE also showed promising results in an infant study. Conclusions, The proposed iMoCo UTE combines self-navigation, motion modeling, and a compressed sensing reconstruction to increase scan efficiency, SNR, and reduce respiratory motion in lung MRI. This proposed strategy shows improvements in free breathing lung MRI scans, especially in very Challenging Application situations, such as pediatric MRI studies.