Prof. Luminita A. Vese Profile

Prof. Luminita A. Vese

at Univ of California Los Angeles

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Author

Publications (11)

Proceedings Article | 12 June 2023 Presentation + Paper

Texture-based optical flow for wind velocity estimation from water vapor data

Joel Barnett, Andrea Bertozzi, Luminita Vese, Igor Yanovsky

Proceedings Volume 12543, 125430H (2023) https://doi.org/10.1117/12.2663008

KEYWORDS: Optical flow, Motion estimation, Spatial resolution, Feature extraction, Satellites, Optical tracking, Image resolution, Equipment, Visualization, Atmospheric sensing, Wind measurement

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Proceedings Article | 1 August 2021 Presentation + Paper

Learning spatial response functions from large multi-sensor AIRS and MODIS datasets

Igor Yanovsky, Thomas Pagano, Evan Manning, Steven Broberg, Hartmut Aumann, Luminita Vese

Proceedings Volume 11829, 118290A (2021) https://doi.org/10.1117/12.2593331

KEYWORDS: Point spread functions, MODIS, Clouds, Satellites, Spatial resolution, Sensors, Infrared radiation, Absorption, Space operations, Mirrors

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Proceedings Article | 14 February 2012 Paper

Placental fetal stem segmentation in a sequence of histology images

Prashant Athavale, Luminita Vese

Proceedings Volume 8314, 83143A (2012) https://doi.org/10.1117/12.911763

KEYWORDS: Image segmentation, Image registration, Blood vessels, Tissues, Diffusion, Image processing, Analytical research, Image processing algorithms and systems, Pathology, Fetus

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Recent research in perinatal pathology argues that analyzing properties of the placenta may reveal important information on how certain diseases progress. One important property is the structure of the placental fetal stems. Analysis of the fetal stems in a placenta could be useful in the study and diagnosis of some diseases like autism. To study the fetal stem structure effectively, we need to automatically and accurately track fetal stems through a sequence of digitized hematoxylin and eosin (H&E) stained histology slides. There are many problems in successfully achieving this goal. A few of the problems are: large size of images, misalignment of the consecutive H&E slides, unpredictable inaccuracies of manual tracing, very complicated texture patterns of various tissue types without clear characteristics, just to name a few. In this paper we propose a novel algorithm to achieve automatic tracing of the fetal stem in a sequence of H&E images, based on an inaccurate manual segmentation of a fetal stem in one of the images. This algorithm combines global affine registration, local non-affine registration and a novel 'dynamic' version of the active contours model without edges. We first use global affine image registration of all the images based on displacement, scaling and rotation. This gives us approximate location of the corresponding fetal stem in the image that needs to be traced. We then use the affine registration algorithm "locally" near this location. At this point, we use a fast non-affine registration based on L²-similarity measure and diffusion regularization to get a better location of the fetal stem. Finally, we have to take into account inaccuracies in the initial tracing. This is achieved through a novel dynamic version of the active contours model without edges where the coefficients of the fitting terms are computed iteratively to ensure that we obtain a unique stem in the segmentation. The segmentation thus obtained can then be used as an initial guess to obtain segmentation in the rest of the images in the sequence. This constitutes an important step in the extraction and understanding of the fetal stem vasculature.

Proceedings Article | 17 March 2011 Paper

Expectation maximization and total variation-based model for computed tomography reconstruction from undersampled data

Ming Yan, Luminita Vese

Proceedings Volume 7961, 79612X (2011) https://doi.org/10.1117/12.878238

KEYWORDS: Computed tomography, Data modeling, Tomography, Radon transform, Reconstruction algorithms, Bismuth, CT reconstruction, Medical imaging, Image restoration, Expectation maximization algorithms

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Proceedings Article | 12 March 2011 Paper

Automated vasculature extraction from placenta images

Nizar Almoussa, Brittany Dutra, Bryce Lampe, Pascal Getreuer, Todd Wittman, Carolyn Salafia, Luminita Vese

Proceedings Volume 7962, 79621L (2011) https://doi.org/10.1117/12.878343

KEYWORDS: Neural networks, Blood vessels, Sensors, Binary data, Image filtering, Roads, Detection and tracking algorithms, Image segmentation, Image processing, Analytical research

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Proceedings Article | 8 February 2011 Paper

An open level set framework for image segmentation and restoration using the Mumford and Shah model

Rami Mohieddine, Luminita Vese

Proceedings Volume 7873, 787309 (2011) https://doi.org/10.1117/12.872457

KEYWORDS: Image segmentation, Image processing algorithms and systems, Differential equations, Partial differential equations, Edge detection, Crystals, Ordinary differential equations, Mathematical modeling, Mathematics, Motion models

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Proceedings Article | 27 March 2009 Paper

Gene to mouse atlas registration using a landmark-based nonlinear elasticity smoother

Tungyou Lin, Carole Le Guyader, Erh-Fang Lee, Ivo Dinov, Paul Thompson, Arthur Toga, Luminita Vese

Proceedings Volume 7259, 72592Q (2009) https://doi.org/10.1117/12.812491

KEYWORDS: Image registration, Data modeling, Brain, Image segmentation, Composites, Medical imaging, Associative arrays, Algorithm development, Brain mapping, Genetics

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Proceedings Article | 3 February 2009 Paper

Sobolev gradients and joint variational image segmentation, denoising, and deblurring

Miyoun Jung, Ginmo Chung, Ganesh Sundaramoorthi, Luminita Vese, Alan Yuille

Proceedings Volume 7246, 72460I (2009) https://doi.org/10.1117/12.806067

KEYWORDS: Image segmentation, Physics, Denoising, Computational imaging, Electronic imaging, Current controlled current source, Mathematical modeling

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Proceedings Article | 26 February 2008 Paper

Functional minimization problems in image processing

Yunho Kim, Luminita Vese

Proceedings Volume 6814, 68140Q (2008) https://doi.org/10.1117/12.775699

KEYWORDS: Image processing, Fourier transforms, Image restoration, Information technology, Computational imaging, Electronic imaging, Inverse problems

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Proceedings Article | 28 February 2007 Paper

An image decomposition model using the total variation and the infinity Laplacian

Christopher Elion, Luminita Vese

Proceedings Volume 6498, 64980W (2007) https://doi.org/10.1117/12.716079

KEYWORDS: Radio over Fiber, Image analysis, Image denoising, Denoising, Partial differential equations, Data modeling, Signal to noise ratio, Computational imaging, Electronic imaging, Mathematical modeling

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Proceedings Article | 2 February 2006 Paper

Computational methods for image restoration, image segmentation, and texture modeling

Ginmo Chung, Triet Le, Linh Lieu, Nicolay Tanushev, Luminita Vese

Proceedings Volume 6065, 60650J (2006) https://doi.org/10.1117/12.659849

KEYWORDS: Image segmentation, Image restoration, Denoising, Brain, Binary data, Radio over Fiber, Data modeling, Tomography, Computational imaging, Magnetic resonance imaging

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Showing 5 of 11 publications

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