Dr. Jon F. Nielsen Profile

Dr. Jon F. Nielsen

Physicist at Univ of Southern California

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Publications (5)

Proceedings Article | 28 April 2005 Paper

Integrated photonic system for optical imaging and spectroscopy: non-invasive monitoring of brain tumor (glioblastoma) angiogenesis

Vishal Saxena, Jon Nielsen, Walter Laug, Marvin Nelson

Proceedings Volume 5693, (2005) https://doi.org/10.1117/12.588720

KEYWORDS: Tumors, Near infrared spectroscopy, Magnetic resonance imaging, Brain, Absorption, Neuroimaging, Tissues, Spectroscopy, Imaging systems, Optical imaging

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Proceedings Article | 14 April 2005 Paper

Relevant information retrieval and fusion of anatomic, physiologic, and metabolic neuroimaging

Stephan Erberich, Jon Nielsen, Ashok Panigrahy, Stefan Bluml, Istvan Seri, Marvin Nelson

Proceedings Volume 5746, (2005) https://doi.org/10.1117/12.595127

KEYWORDS: Magnetic resonance imaging, Functional magnetic resonance imaging, Neuroimaging, Diffusion tensor imaging, Brain, Information fusion, Data storage, Visualization, Picture Archiving and Communication System, Diffusion

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Proceedings Article | 30 April 2004 Paper

Neurodevelopment assessment of newborns with combined fMRI and DTI

Stephan Erberich, Jon Nielsen, Stefan Bluml, Philippe Friedlich, Istvan Seri, Marvin Nelson

Proceedings Volume 5369, (2004) https://doi.org/10.1117/12.536236

KEYWORDS: Functional magnetic resonance imaging, Diffusion tensor imaging, Brain, Neuroimaging, Magnetic resonance imaging, Brain mapping, Visualization, Sensors, Functional imaging, Cortical activation

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Functional Magnetic Resonance Imaging (fMRI) provides the location and regional extent of a task correlated activation in the brain. Recently we have demonstrated, that fMRI of passive sensory tasks (visual, auditory, motor) can be successfully used to map cortical activation in the newborn brain. However the interpretation of the functional response in the immature brain is difficult, as the blood oxygen level dependent (BOLD) physiological signal and location of the activation is quite different compared to adult fMRI responses of similar tasks. We expect, that the major reason for these differences are primarily caused by the immature myelination of the white matter tracts at this age. Diffusion tensor imaging (DTI) can be used to measure the white matter tract development in the newborn brain. The purpose of this paper is to report how to obtain and to combine fMRI and DTI data processing to enhance functional brain mapping in newborns. We obtained simultaneous fMRI and DTI data of 18 newborns, post-conceptional age (gestational age at study) between 34-week and 52-week, which were referred for clinical indicated MRI. 16 out of 18 subjects have been successfully investigated with combined fMRI and DTI and functional activation could be obtained. Fiber tracking was successfully in the visual and auditory cortex, but proofed difficult in the motor-cortex. The additional tract information supported the functional findings and the interpretation in the immature brain. The novel functional imaging in newborn is challenging because of the yet unknown physiological response and location of activation in the newborn brain. Therefore one need additional evidence that the functional findings are valid in the context of structural development. The maturation of myelination is an essential information to compare and to interpret fMRI in newborns. We conclude that the proposed method of combined fMRI and DTI, derived from adult neuroimaging, will be most relevant to understand the physiological response and thus the neurodevelopment of the newborn brain.

Proceedings Article | 30 April 2004 Paper

Diffusion tensor imaging in newborns

Jon Nielsen, Ashok Panigrahy, Stephan Erberich

Proceedings Volume 5369, (2004) https://doi.org/10.1117/12.536240

KEYWORDS: Diffusion tensor imaging, Brain, Diffusion, Magnetic resonance imaging, Neodymium, 3D metrology, Anisotropy, Image registration, Neuroimaging, 3D image processing

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Proceedings Article | 19 May 2003 Paper

Image matching as a diagnostic support tool

Jon Nielsen, Marvin Nelson, Fei Cao, Lifeng Liu, H. Huang

Proceedings Volume 5033, (2003) https://doi.org/10.1117/12.487790

KEYWORDS: Databases, Diagnostics, Magnetic resonance imaging, Medical imaging, Brain, Neuroimaging, Brain diseases, Image processing, Image retrieval, Computer aided diagnosis and therapy

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