Dang, H; Stayman, J W; Sisniega, A; Xu, J; Zbijewski, W; Wang, X; Foos, D H; Aygun, N; Koliatsos, V E; Siewerdsen, J H
Statistical reconstruction for cone-beam CT with a post-artifact-correction noise model: Application to high-quality head imaging Journal Article
In: Physics in Medicine and Biology, vol. 60, no. 16, pp. 6153–6175, 2015.
Abstract | Links | BibTeX | Tags: artifact correction, brain, Computerized tomography, cone-beam CT, Flat panel displays, image processing, Image quality, Image reconstruction, Intensive care units, intracranial hemorrhage, Intracranial hemorrhages, Iterative methods, Least squares approximations, Measurement Noise, measurement noise model, Model based iterative reconstruction, model-based iterative reconstruction, Soft tissue, soft-tissue image quality, Tissue, Traumatic Brain Injuries, traumatic brain injury
@article{Dang2015,
title = {Statistical reconstruction for cone-beam CT with a post-artifact-correction noise model: Application to high-quality head imaging},
author = {Dang, H and Stayman, J W and Sisniega, A and Xu, J and Zbijewski, W and Wang, X and Foos, D H and Aygun, N and Koliatsos, V E and Siewerdsen, J H},
doi = {10.1088/0031-9155/60/16/6153},
year = {2015},
date = {2015-01-01},
journal = {Physics in Medicine and Biology},
volume = {60},
number = {16},
pages = {6153--6175},
abstract = {Non-contrast CT reliably detects fresh blood in the brain and is the current front-line imaging modality for intracranial hemorrhage such as that occurring in acute traumatic brain injury (contrast ∼40-80 HU, size \> 1 mm). We are developing flat-panel detector (FPD) cone-beam CT (CBCT) to facilitate such diagnosis in a low-cost, mobile platform suitable for point-of-care deployment. Such a system may offer benefits in the ICU, urgent care/concussion clinic, ambulance, and sports and military theatres. However, current FPD-CBCT systems face significant challenges that confound low-contrast, soft-tissue imaging. Artifact correction can overcome major sources of bias in FPD-CBCT but imparts noise amplification in filtered backprojection (FBP). Model-based reconstruction improves soft-tissue image quality compared to FBP by leveraging a high-fidelity forward model and image regularization. In this work, we develop a novel penalized weighted least-squares (PWLS) image reconstruction method with a noise model that includes accurate modeling of the noise characteristics associated with the two dominant artifact corrections (scatter and beam-hardening) in CBCT and utilizes modified weights to compensate for noise amplification imparted by each correction. Experiments included real data acquired on a FPD-CBCT test-bench and an anthropomorphic head phantom emulating intra-parenchymal hemorrhage. The proposed PWLS method demonstrated superior noise-resolution tradeoffs in comparison to FBP and PWLS with conventional weights (viz. at matched 0.50 mm spatial resolution},
keywords = {artifact correction, brain, Computerized tomography, cone-beam CT, Flat panel displays, image processing, Image quality, Image reconstruction, Intensive care units, intracranial hemorrhage, Intracranial hemorrhages, Iterative methods, Least squares approximations, Measurement Noise, measurement noise model, Model based iterative reconstruction, model-based iterative reconstruction, Soft tissue, soft-tissue image quality, Tissue, Traumatic Brain Injuries, traumatic brain injury},
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Davis, A E
Mechanisms of traumatic brain injury: biomechanical, structural and cellular considerations Journal Article
In: Critical Care Nursing Quarterly, vol. 23, no. 3, pp. 1–13, 2000.
Abstract | BibTeX | Tags: *Brain Injuries/pa [Pathology], *Brain Injuries/pp [Physiopathology], Biomechanical Phenomena, Brain Injuries/cl [Classification], Brain Injuries/co [Complications], Brain/me [Metabolism], Brain/pa [Pathology], Humans, intracranial hemorrhage, Neurons/me [Metabolism], Neurons/pa [Pathology], Nonpenetrating/pa [Pathology], Nonpenetrating/pp [Physiopathology], Skull Fractures/pa [Pathology], Skull Fractures/pp [Physiopathology], Traumatic/pa [Pathology], Traumatic/pp [Physiopatho, Wounds
@article{Davis2000,
title = {Mechanisms of traumatic brain injury: biomechanical, structural and cellular considerations},
author = {Davis, A E},
year = {2000},
date = {2000-01-01},
journal = {Critical Care Nursing Quarterly},
volume = {23},
number = {3},
pages = {1--13},
abstract = {Traumatic brain injury (TBI) is a public health problem of great concern, because it affects more than 2 million individuals each year. TBI occurs as a result of motor vehicle crashes, falls, and sports-related events. Biomechanical mechanisms occurring at the time of the injury initiate primary and secondary injuries that evolve over several days. In this article the relationship between an blunt injury event and the subsequent damage produced is addressed. Mechanisms of brain injury from biomechanics to cellular pathobiology are presented. Primary and secondary injuries are differentiated, and specific focal and diffuse clinical syndromes are described. Cellular mechanisms responsible for injury are also addressed, because they provide the unifying concepts across the many clinical syndromes so often discussed separately in reviews of traumatic brain injury. [References: 26]},
keywords = {*Brain Injuries/pa [Pathology], *Brain Injuries/pp [Physiopathology], Biomechanical Phenomena, Brain Injuries/cl [Classification], Brain Injuries/co [Complications], Brain/me [Metabolism], Brain/pa [Pathology], Humans, intracranial hemorrhage, Neurons/me [Metabolism], Neurons/pa [Pathology], Nonpenetrating/pa [Pathology], Nonpenetrating/pp [Physiopathology], Skull Fractures/pa [Pathology], Skull Fractures/pp [Physiopathology], Traumatic/pa [Pathology], Traumatic/pp [Physiopatho, Wounds},
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Dang, H; Stayman, J W; Sisniega, A; Xu, J; Zbijewski, W; Wang, X; Foos, D H; Aygun, N; Koliatsos, V E; Siewerdsen, J H
Statistical reconstruction for cone-beam CT with a post-artifact-correction noise model: Application to high-quality head imaging Journal Article
In: Physics in Medicine and Biology, vol. 60, no. 16, pp. 6153–6175, 2015.
@article{Dang2015,
title = {Statistical reconstruction for cone-beam CT with a post-artifact-correction noise model: Application to high-quality head imaging},
author = {Dang, H and Stayman, J W and Sisniega, A and Xu, J and Zbijewski, W and Wang, X and Foos, D H and Aygun, N and Koliatsos, V E and Siewerdsen, J H},
doi = {10.1088/0031-9155/60/16/6153},
year = {2015},
date = {2015-01-01},
journal = {Physics in Medicine and Biology},
volume = {60},
number = {16},
pages = {6153--6175},
abstract = {Non-contrast CT reliably detects fresh blood in the brain and is the current front-line imaging modality for intracranial hemorrhage such as that occurring in acute traumatic brain injury (contrast ∼40-80 HU, size \> 1 mm). We are developing flat-panel detector (FPD) cone-beam CT (CBCT) to facilitate such diagnosis in a low-cost, mobile platform suitable for point-of-care deployment. Such a system may offer benefits in the ICU, urgent care/concussion clinic, ambulance, and sports and military theatres. However, current FPD-CBCT systems face significant challenges that confound low-contrast, soft-tissue imaging. Artifact correction can overcome major sources of bias in FPD-CBCT but imparts noise amplification in filtered backprojection (FBP). Model-based reconstruction improves soft-tissue image quality compared to FBP by leveraging a high-fidelity forward model and image regularization. In this work, we develop a novel penalized weighted least-squares (PWLS) image reconstruction method with a noise model that includes accurate modeling of the noise characteristics associated with the two dominant artifact corrections (scatter and beam-hardening) in CBCT and utilizes modified weights to compensate for noise amplification imparted by each correction. Experiments included real data acquired on a FPD-CBCT test-bench and an anthropomorphic head phantom emulating intra-parenchymal hemorrhage. The proposed PWLS method demonstrated superior noise-resolution tradeoffs in comparison to FBP and PWLS with conventional weights (viz. at matched 0.50 mm spatial resolution},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Davis, A E
Mechanisms of traumatic brain injury: biomechanical, structural and cellular considerations Journal Article
In: Critical Care Nursing Quarterly, vol. 23, no. 3, pp. 1–13, 2000.
@article{Davis2000,
title = {Mechanisms of traumatic brain injury: biomechanical, structural and cellular considerations},
author = {Davis, A E},
year = {2000},
date = {2000-01-01},
journal = {Critical Care Nursing Quarterly},
volume = {23},
number = {3},
pages = {1--13},
abstract = {Traumatic brain injury (TBI) is a public health problem of great concern, because it affects more than 2 million individuals each year. TBI occurs as a result of motor vehicle crashes, falls, and sports-related events. Biomechanical mechanisms occurring at the time of the injury initiate primary and secondary injuries that evolve over several days. In this article the relationship between an blunt injury event and the subsequent damage produced is addressed. Mechanisms of brain injury from biomechanics to cellular pathobiology are presented. Primary and secondary injuries are differentiated, and specific focal and diffuse clinical syndromes are described. Cellular mechanisms responsible for injury are also addressed, because they provide the unifying concepts across the many clinical syndromes so often discussed separately in reviews of traumatic brain injury. [References: 26]},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Dang, H; Stayman, J W; Sisniega, A; Xu, J; Zbijewski, W; Wang, X; Foos, D H; Aygun, N; Koliatsos, V E; Siewerdsen, J H
Statistical reconstruction for cone-beam CT with a post-artifact-correction noise model: Application to high-quality head imaging Journal Article
In: Physics in Medicine and Biology, vol. 60, no. 16, pp. 6153–6175, 2015.
Abstract | Links | BibTeX | Tags: artifact correction, brain, Computerized tomography, cone-beam CT, Flat panel displays, image processing, Image quality, Image reconstruction, Intensive care units, intracranial hemorrhage, Intracranial hemorrhages, Iterative methods, Least squares approximations, Measurement Noise, measurement noise model, Model based iterative reconstruction, model-based iterative reconstruction, Soft tissue, soft-tissue image quality, Tissue, Traumatic Brain Injuries, traumatic brain injury
@article{Dang2015,
title = {Statistical reconstruction for cone-beam CT with a post-artifact-correction noise model: Application to high-quality head imaging},
author = {Dang, H and Stayman, J W and Sisniega, A and Xu, J and Zbijewski, W and Wang, X and Foos, D H and Aygun, N and Koliatsos, V E and Siewerdsen, J H},
doi = {10.1088/0031-9155/60/16/6153},
year = {2015},
date = {2015-01-01},
journal = {Physics in Medicine and Biology},
volume = {60},
number = {16},
pages = {6153--6175},
abstract = {Non-contrast CT reliably detects fresh blood in the brain and is the current front-line imaging modality for intracranial hemorrhage such as that occurring in acute traumatic brain injury (contrast ∼40-80 HU, size \> 1 mm). We are developing flat-panel detector (FPD) cone-beam CT (CBCT) to facilitate such diagnosis in a low-cost, mobile platform suitable for point-of-care deployment. Such a system may offer benefits in the ICU, urgent care/concussion clinic, ambulance, and sports and military theatres. However, current FPD-CBCT systems face significant challenges that confound low-contrast, soft-tissue imaging. Artifact correction can overcome major sources of bias in FPD-CBCT but imparts noise amplification in filtered backprojection (FBP). Model-based reconstruction improves soft-tissue image quality compared to FBP by leveraging a high-fidelity forward model and image regularization. In this work, we develop a novel penalized weighted least-squares (PWLS) image reconstruction method with a noise model that includes accurate modeling of the noise characteristics associated with the two dominant artifact corrections (scatter and beam-hardening) in CBCT and utilizes modified weights to compensate for noise amplification imparted by each correction. Experiments included real data acquired on a FPD-CBCT test-bench and an anthropomorphic head phantom emulating intra-parenchymal hemorrhage. The proposed PWLS method demonstrated superior noise-resolution tradeoffs in comparison to FBP and PWLS with conventional weights (viz. at matched 0.50 mm spatial resolution},
keywords = {artifact correction, brain, Computerized tomography, cone-beam CT, Flat panel displays, image processing, Image quality, Image reconstruction, Intensive care units, intracranial hemorrhage, Intracranial hemorrhages, Iterative methods, Least squares approximations, Measurement Noise, measurement noise model, Model based iterative reconstruction, model-based iterative reconstruction, Soft tissue, soft-tissue image quality, Tissue, Traumatic Brain Injuries, traumatic brain injury},
pubstate = {published},
tppubtype = {article}
}
Davis, A E
Mechanisms of traumatic brain injury: biomechanical, structural and cellular considerations Journal Article
In: Critical Care Nursing Quarterly, vol. 23, no. 3, pp. 1–13, 2000.
Abstract | BibTeX | Tags: *Brain Injuries/pa [Pathology], *Brain Injuries/pp [Physiopathology], Biomechanical Phenomena, Brain Injuries/cl [Classification], Brain Injuries/co [Complications], Brain/me [Metabolism], Brain/pa [Pathology], Humans, intracranial hemorrhage, Neurons/me [Metabolism], Neurons/pa [Pathology], Nonpenetrating/pa [Pathology], Nonpenetrating/pp [Physiopathology], Skull Fractures/pa [Pathology], Skull Fractures/pp [Physiopathology], Traumatic/pa [Pathology], Traumatic/pp [Physiopatho, Wounds
@article{Davis2000,
title = {Mechanisms of traumatic brain injury: biomechanical, structural and cellular considerations},
author = {Davis, A E},
year = {2000},
date = {2000-01-01},
journal = {Critical Care Nursing Quarterly},
volume = {23},
number = {3},
pages = {1--13},
abstract = {Traumatic brain injury (TBI) is a public health problem of great concern, because it affects more than 2 million individuals each year. TBI occurs as a result of motor vehicle crashes, falls, and sports-related events. Biomechanical mechanisms occurring at the time of the injury initiate primary and secondary injuries that evolve over several days. In this article the relationship between an blunt injury event and the subsequent damage produced is addressed. Mechanisms of brain injury from biomechanics to cellular pathobiology are presented. Primary and secondary injuries are differentiated, and specific focal and diffuse clinical syndromes are described. Cellular mechanisms responsible for injury are also addressed, because they provide the unifying concepts across the many clinical syndromes so often discussed separately in reviews of traumatic brain injury. [References: 26]},
keywords = {*Brain Injuries/pa [Pathology], *Brain Injuries/pp [Physiopathology], Biomechanical Phenomena, Brain Injuries/cl [Classification], Brain Injuries/co [Complications], Brain/me [Metabolism], Brain/pa [Pathology], Humans, intracranial hemorrhage, Neurons/me [Metabolism], Neurons/pa [Pathology], Nonpenetrating/pa [Pathology], Nonpenetrating/pp [Physiopathology], Skull Fractures/pa [Pathology], Skull Fractures/pp [Physiopathology], Traumatic/pa [Pathology], Traumatic/pp [Physiopatho, Wounds},
pubstate = {published},
tppubtype = {article}
}