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Talita Perciano

Talita
Talita Perciano
Research Scientist
Computational Research Division
Phone: +1 510 486 5060
1 Cyclotron
Mail Stop 59R3103 - 059-3034B
Berkeley, California 94720 US

Talita Perciano is a Research Scientist at Lawrence Berkeley National Laboratory, and a Computer Vision consultant for the National Energy Research Scientific Computing Center (NERSC). She is also part of the Image Analysis team of the Center of Applied Mathematics for Energy Related Applications (CAMERA). Her current knowledge is image processing and pattern recognition applied to different image data, allied to HPC. Relevant research includes: filamentous structures segmentation and quantification using Markov Random Fields (2D ocular fundus photography, plant roots in soil profile images, roads/rivers in satellite images), brain imaging (CT, MRI), vibro-acoustography image formation and restoration, among others. She has been working on computer vision algorithms and statistical computing the past 10 years, and she is a developer of R packages, a software environment for statistical computing and graphics, for image processing and analysis. She earned her doctorate in Computer Science from the University of São Paulo in 2012.

[More info about research projects]

Selected publications:

  • Talita Perciano, Daniela Ushizima, Harinarayan Krishnan,Dilworth Parkinson, Natalie Larson, Daniël M. Pelt, Wes Bethel, Frank Zok and James Sethian. Insight into 3D micro-CT data: exploring segmentation algorithms through performance metrics. Journal of Synchrotron Radiation, 24(5), September 2017
  • Maryam Farmand, Richard Celestre, Peter Denes, A. L. David Kilcoyne, Stefano Marchesini, Howard Padmore, Tolek Tyliszczak, Tony Warwick, Xiaowen Shi, James Lee, Young-Sang Yu, Jordi Cabana, John Joseph, Harinarayan Krishnan, Talita Perciano, Filipe R. N. C. Maia, and David A. Shapiro. Near-edge x-ray refraction fine structure microscopy. Applied Physics Letters, 110(6):063101, February 2017
  • Benedikt J. Daurer, Hari Krishnan, Talita Perciano, Filipe R. N. C. Maia, David A. Shapiro, James A. Sethian, and Stefano Marchesini. Nanosurveyor: a framework for real-time data processing. Advanced Structural and Chemical Imaging, 3(1):7, January 2017
  • D. M. Ushizima, H. A. Bale, E. W. Bethel, P. Ercius, B. A. Helms, H. Krishnan, L. T. Grinberg, M. Haranczyk, A. A. Macdowell, K. Odziomek, D. Y. Parkinson, T. Perciano, R. O. Ritchie, and C. Yang. IDEAL: Images Across Domains, Experiments, Algorithms and Learning. JOM - The Journal of The Minerals, Metals & Materials Society (TMS), pages 1-10, September 2016
  • T. Perciano, D. M. Ushizima, E. W. Bethel, Y. D. Mizrahi, D. Parkinson, and J. A. Sethian. Reduced-complexity image segmentation under parallel markov random eld formulation using graph partitioning. In 2016 IEEE International Conference on Image Processing (ICIP), pages 1259-1263, September 2016
  • S. Marchesini, H. Krishnan, D. A. Shapiro, T. Perciano, J. A. Sethian, B. J. Daurer, and F. R. N. C. Maia. SHARP: a distributed, GPU-based ptychographic solver. Accepted to Journal of Applied Crystallography, 2016
  • T. Perciano, F. Tupin, R. Hirata Jr., and R. M. Cesar Jr. A Two-level Markov Random Field for Road Network Extraction and its Application with Optical, SAR and Multitemporal Data. International Journal of Remote Sensing, 37(16):3584-3610, 2016
  • Dilworth Y. Parkinson, Keith Beattie, Xian Chen, Joaquin Correa, Eli Dart, Benedikt J. Daurer, Jack R. Deslippe, Alexander Hexemer, Harinarayan Krishnan, Alastair A. MacDowell, Filipe R. N. C. Maia, Stefano Marchesini, Howard A. Padmore, Simon J. Patton, Talita Perciano, James A. Sethian, David Shapiro, Rune Stromsness, Nobumichi Tamura, Brian L. Tierney, Craig E. Tull, and Daniela Ushizima. Real-time data-intensive computing. AIP Conference Proceedings, 1741(1), July 2016
  • Andrew W. Wills, David J. Michalak, Peter Ercius, Ethan R. Rosenberg, Talita Perciano, Daniela Ushizima, Rory Runser, and Brett A. Helms. Block copolymer packing limits and interfacial reconfigurability in the assembly of periodic mesoporous organosilicas. Advanced Functional Materials, 25(26):4120–4128, 2015
  • J. Donatelli, M. Haranczyk, A. Hexemer, H. Krishnan, X. Li, L. Lin, F. Maia, S. Marchesini, D. Parkinson, T. Perciano, D. Shapiro, D. Ushizima, C. Yang, and J.A. Sethian. Camera: The center for advanced mathematics for energy research applications. Synchrotron Radiation News, 28(2):4–9, 2015
  • D. Ushizima, T. Perciano, and D. Parkinson. Fast detection of material deformation through structural dissimilarity. In Big Data (Big Data), 2015 IEEE International Conference on, pages 2775-2781, October 2015
  • D. Ushizima, T. Perciano, H. Krishnan, B. Loring, H. Bale, D. Parkinson, and J. Sethian. Structure recognition from high resolution images of ceramic composites. In Big Data (Big Data), 2014 IEEE International Conference on, pages 683–691, Oct 2014
  • T. Perciano. Image analysis and statistics: an introduction using R and RIPA. In The International R Users Conference - Contributed Works, pages 65–65, 2014
  • T. Perciano, M. W. Urban, N. D. A. Mascarenhas, M. Fatemi, A. C. Frery, and G. T. Silva. Deconvolution of vibroacoustic images using a simulation model based on a three dimensional point spread function. Ultrasonics, 53(1):36 – 44, 2013.
  • A. C. Frery and T. Perciano. Introduction to Image Processing Using R: learning by examples (SpringerBriefs). Springer, 1 edition, 2013. ISBN: 978-1447149491.
  • T. Perciano, R. Hirata Jr., R. M. Cesar Jr. Detection of Thin and Ramified Structure in Images using Markov Random Fields and Perceptual Information. In XXVI Conference on Graphics, Patterns and Images, 2013, Arequipa. Workshop of Theses and Dissertations (WTD) in SIBGRAPI 2013, pages 1-6, 2013.
  • H. Sportouche, C.-A. Deledalle, J.-M. Nicolas, F. Tupin, and T. Perciano. How to combine terrasar-x and cosmo-skymed high-resolution images for a better scene understanding? In Geoscience and Remote Sensing Symposium (IGARSS), 2012 IEEE International, july 2012.
  • T. Perciano and G. T. Silva. Deconvolution of Vibroacoustic images with a 3D Point-spread Function. In Proceedings of the XXIII Brazilian Congress on Biomedical Engineering, CBEB ’12, 2012.
  • T. Perciano, F. Tupin, R. Hirata, and R.M. Cesar. A hierarchical markov random field for road network extraction and its application with optical and SAR data. In Geoscience and Remote Sensing Symposium (IGARSS), 2011 IEEE International, pages 1159 –1162, july 2011.
  • T. Perciano, R. Hirata Jr., L. A. de C. Jorge. Parameter Estimation for Ridge Detection in Images with Thin Structures. In 15th Iberoamerican Congress on Pattern Recognition, 2010, Sao Paulo. CIARP 2010, Lecture Notes in Computer Science. Heidelberg: Springer, 2010, v.6419, p. 386-393.
  • T. Perciano, R. Hirata Jr., L. A. de C. Jorge. Ridge Linking using an Adaptive Oriented Mask Applied to Plant Root Images with Thin Structures. In 15th Iberoamerican Congress on Pattern Recognition, 2010, Sao Paulo. CIARP 2010, Lecture Notes in Computer Science. Heidelberg: Springer, 2010, v.6419, p. 378-385.