22,811 research outputs found
Framework for quantitative evaluation of 3D vessel segmentation approaches using vascular phantoms in conjunction with 3D landmark localization and registration
No full textMartin Andersen Nexø
No full textThis is a short presentation of the main works of the Danish author Martin Andersen Nexø
White matter fiber-based analysis of T1w/T2w ratio map
No full textPurpose: To develop, test, evaluate and apply a novel tool for the white matter fiber-based analysis of T1w/T2w ratio maps quantifying myelin content. Background: The cerebral white matter in the human brain develops from a mostly non-myelinated state to a nearly fully mature white matter myelination within the first few years of life. High resolution T1w/T2w ratio maps are believed to be effective in quantitatively estimating myelin content on a voxel-wise basis. We propose the use of a fiber-tract-based analysis of such T1w/T2w ratio data, as it allows us to separate fiber bundles that a common regional analysis imprecisely groups together, and to associate effects to specific tracts rather than large, broad regions. Methods: We developed an intuitive, open source tool to facilitate such fiber-based studies of T1w/T2w ratio maps. Via its Graphical User Interface (GUI) the tool is accessible to non-technical users. The framework uses calibrated T1w/T2w ratio maps and a prior fiber atlas as an input to generate profiles of T1w/T2w values. The resulting fiber profiles are used in a statistical analysis that performs along-tract functional statistical analysis. We applied this approach to a preliminary study of early brain development in neonates. Results: We developed an open-source tool for the fiber based analysis of T1w/T2w ratio maps and tested it in a study of brain development
Improved registration of DCE-MR images of the liver using a prior segmentation of the region of interest
No full textIn Dynamic Contrast-Enhanced MRI (DCE-MRI) of the liver, a series of images is acquired over a period of 20 minutes. Due to the patient's breathing, the liver is subject to a substantial displacement between acquisitions. Furthermore, due to its location in the abdomen, the liver also undergoes marked deformation. The large deformations combined with variation in image contrast make accurate liver registration challenging. We present a registration framework that incorporates a liver segmentation to improve the registration accuracy. The segmented liver serves as region-of-interest to our in-house developed registration method called ALOST (autocorrelation of local image structure). ALOST is a continuous optimization method that uses local phase features to overcome space-variant intensity distortions. The proposed framework can confine the solution field to the liver and allow for ALOST to obtain a more accurate solution. For the segmentation part, we use a level-set method to delineate the liver in a so-called contrast enhancement map. This map is obtained by computing the difference between the last and registered first volume from the DCE series. Subsequently, we slightly dilate the segmentation, and apply it as the mask to the other DCE-MRI volumes during registration. It is shown that the registration result becomes more accurate compared with the original ALOST approach.ImPhys/Quantitative Imagin
Automatic estimation of retinal nerve fiber bundle orientation in SD-OCT images using a structure-oriented smoothing filter
No full textOptical coherence tomography (OCT) yields high-resolution, three-dimensional images of the retina. A better understanding of retinal nerve fiber bundle (RNFB) trajectories in combination with visual field data may be used for future diagnosis and monitoring of glaucoma. However, manual tracing of these bundles is a tedious task. In this work, we present an automatic technique to estimate the orientation of RNFBs from volumetric OCT scans. Our method consists of several steps, starting from automatic segmentation of the RNFL. Then, a stack of en face images around the posterior nerve fiber layer interface was extracted. The image showing the best visibility of RNFB trajectories was selected for further processing. After denoising the selected en face image, a semblance structure-oriented filter was applied to probe the strength of local linear structure in a discrete set of orientations creating an orientation space. Gaussian filtering along the orientation axis in this space is used to find the dominant orientation. Next, a confidence map was created to supplement the estimated orientation. This confidence map was used as pixel weight in normalized convolution to regularize the semblance filter response after which a new orientation estimate can be obtained. Finally, after several iterations an orientation field corresponding to the strongest local orientation was obtained. The RNFB orientations of six macular scans from three subjects were estimated. For all scans, visual inspection shows a good agreement between the estimated orientation fields and the RNFB trajectories in the en face images. Additionally, a good correlation between the orientation fields of two scans of the same subject was observed. Our method was also applied to a larger field of view around the macula. Manual tracing of the RNFB trajectories shows a good agreement with the automatically obtained streamlines obtained by fiber tracking.ImPhys/Quantitative Imagin
Multi-voxel algorithm for quantitative bi-exponential MRI T<sub>1</sub> estimation
No full textQuantification of the spin-lattice relaxation time, T1, of tissues is important for characterization of tissues in clinical magnetic resonance imaging (MRI). In T1 mapping, T1 values are estimated from a set of T1-weighted MRI images. Due to the limited spatial resolution of the T1-weighted images, one voxel might consist of two tissues, causing partial volume effects (PVE). In conventional mono-exponential T1 estimation, these PVE result in systematic errors in the T1 map. To account for PVE, single-voxel bi-exponential estimators have been suggested. Unfortunately, in general, they suffer from low accuracy and precision. In this work, we propose a joint multi-voxel bi-exponential T1 estimator (JMBE) and compare its performance to a single-voxel bi-exponential T1 estimator (SBE). Results show that, in contrast to the SBE, and for clinically achievable single-voxel SNRs, the JMBE is accurate and efficient if four or more neighboring voxels are used in the joint estimation framework. This illustrates that, for clinically realistic SNRs, accurate results for quantitative biexponential T1 estimation are only achievable if information of neighboring voxels is incorporated.Team Michel Verhaege
Loosely coupled level sets for retinal layers and drusen segmentation in subjects with dry age-related macular degeneration
No full textOptical coherence tomography (OCT) is used to produce high-resolution three-dimensional images of the retina, which permit the investigation of retinal irregularities. In dry age-related macular degeneration (AMD), a chronic eye disease that causes central vision loss, disruptions such as drusen and changes in retinal layer thicknesses occur which could be used as biomarkers for disease monitoring and diagnosis. Due to the topology disrupting pathology, existing segmentation methods often fail. Here, we present a solution for the segmentation of retinal layers in dry AMD subjects by extending our previously presented loosely coupled level sets framework which operates on attenuation coefficients. In eyes affected by AMD, Bruch’s membrane becomes visible only below the drusen and our segmentation framework is adapted to delineate such a partially discernible interface. Furthermore, the initialization stage, which tentatively segments five interfaces, is modified to accommodate the appearance of drusen. This stage is based on Dijkstra's algorithm and combines prior knowledge on the shape of the interface, gradient and attenuation coefficient in the newly proposed cost function. This prior knowledge is incorporated by varying the weights for horizontal, diagonal and vertical edges. Finally, quantitative evaluation of the accuracy shows a good agreement between manual and automated segmentation.ImPhys/Quantitative Imagin
Louis A. Martin-Vega
No full textDr. Louis A. Martin-Vega has served as Dean of the College of Engineering at North Carolina State University in Raleigh, North Carolina since 2006. With over 10,000 students, 750 faculty and staff and $200M in annual research expenditures, NC State’s College of Engineering is internationally recognized for the excellence of its research and educational programs. Prior to joining NC State, he spent five years as dean of engineering at the University of South Florida in Tampa, Florida. He has also held several prestigious positions at the National Science Foundation (NSF) including acting head of its Engineering Directorate and director of its Division of Design, Manufacture and Industrial Innovation. His research and teaching interests are in the areas of industrial engineering, manufacturing, logistics and distribution, operations management and production and service systems. He is the author or co-author of more than 100 journal articles, book chapters and other publications and has made over 200 keynote and related presentations at national and international forums.
Martin-Vega is a Fellow of the Institute of Industrial Engineers (IIE) and the Society of Manufacturing Engineers (SME). His numerous awards include the 1999 IIE Albert Holzman Distinguished Educator Award, the 2000 HENACC-Hispanic Engineering National Education Achievement Award, the 2007 National Hispanic Scientist of the Year Award from the Tampa Museum of Science and Industry, the 2008 Outstanding Engineer in North Carolina Award from the NC Society of Engineers, the Industrial and Systems Engineering Alumni Leadership Award from the University of Florida in 2009, and the 2012 Frank and Lillian Gilbreth Industrial Engineering Award, IIE’s highest honor. He is a past president of IIE, a member of the Pan American Academy of Engineering and the HENACC Hall of Fame and was named as one of the 50 Most Influential Hispanics in the US by Hispanic Business magazine in 2014. He is a former member of the executive board of the National GEM Consortium and former chair of the ASEE Engineering Deans Council. He is currently the Immediate Past President of ASEE, past Chair of the Advisory Committee for the Engineering Directorate at NSF and current Vice-Chair of NSF’s Foundation-Wide Committee on Equal Opportunities in Science and Engineering (CEOSE).
Martin-Vega holds a B.S. in industrial engineering from the University of Puerto Rico at Mayaguez, an M.S. in operations research from New York University and M.E. and Ph.D. degrees in industrial and systems engineering from the University of Florida.https://commons.erau.edu/asee-se-bios/1002/thumbnail.jp
Deformable image registration with a featurelet algorithm: implementation as a 3D-slicer extension and validation
No full textA radiotherapy (RT) treatment can last for several weeks. In that time organ motion and shape changes introduce uncertainty in dose application. Monitoring and quantifying the change can yield a more precise irradiation margin definition and thereby reduce dose delivery to healthy tissue and adjust tumor targeting. Deformable image registration (DIR) has the potential to fulfill this task by calculating a deformation field (DF) between a planning CT and a repeated CT of the altered anatomy. Application of the DF on the original contours yields new contours that can be used for an adapted treatment plan. DIR is a challenging method and therefore needs careful user interaction. Without a proper graphical user interface (GUI) a misregistration cannot be easily detected by visual inspection and the results cannot be fine-tuned by changing registration parameters. To provide a DIR algorithm with such a GUI available for everyone, we created the extension Featurelet-Registration for the open source software p atform 3D Slicer. The registration logic is an upgrade of an in-house-developed DIR method, which is a featurelet-based piecewise rigid registration. The so called "featurelets" are equally sized rectangular subvolumes of the moving image which are rigidly registered to rectangular search regions on the fixed image. The output is a deformed image and a deformation field. Both can be visualized directly in 3D Slicer facilitating the interpretation and quantification of the results. For validation of the registration accuracy two deformable phantoms were used. The performance was benchmarked against a demons algorithm with comparable results.</p
Jack Alive / Martin Dead : The Location of the "Author" in Jack London\u27s Martin Eden
No full textThis essay is an attempt to read Martin Eden, Jack Londonʼs autobiographical novel, in terms of the inextricable relationship between the author and the protagonist. Critics have often taken the unbalanced plot and the lack of ironic distance between narrator and character in Martin Eden as the technical weakness of London, but this paper argues that the achievement of this novel owes a great deal to the attachment of London to Martin. The unbalanced structure is a necessary product of the severe struggle of the author to kill his romantic alter ego. // Martin, who aspires to win Ruth Morse, tries to cross class boundaries by making a career of a writer. Even after realizing the emptiness of Ruth, who turns out to be nothing but a typical figure of the bourgeoisie, he somehow persists in loving her. The notion underlying here is that, for Martin, love, career and art are fundamentally inseparable. He objects to the aestheteʼs view of Brissenden on account of his separation of art from career. Martinʼs identity and life consist only in the triunity of love/career/art; the alternative is the repudiation of life. Thus, the unnatural delay of his disappointment in love can be regarded as Londonʼs strategy to set the suicide of Martin as the necessary consequence of the story. // By finishing the story and killing Martin, London finally detaches himself from Martin, reconstructs his self, and, unlike Martin, survives as a professional writer. In this sense, Martin Eden is a story about “writerʼs self-reconstruction.
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