Dilano Saldin, Building 6-1105, Thursday, May 12, 2016  1PM 



      Structure from Angular Correlations

Dilano Saldin, Dept. of Physics, University of Wisconsin, Milwaukee


The x-ray free electron laser XFEL provides a quantum leap in brightness over all previous x-ray sources. The problem is that particles (usually single molecules or viruses) are injected in the beam in random unknown orientations. Ideal would be to measure a quantity that is dependent on the structure but not on the orientations. If so this would provide all the advantages of multiple particles that is afforded by a crystal of trillions of molecules, except they don't have to be perfectly aligned as in a crystal. This may allow the unprecedented ability to study chemical reactions as they are expected to occur in nature, amongst unaligned molecules.

Jeffrey Donatelli, Building 70A-3377, Monday, May 2, 2016 2PM 

Jeffrey Donatelli is a postdoctoral fellow in the Mathematics Group at LBNL and in the Department of Mathematics, University of California, Berkeley. He received a PhD in applied mathematics from UC Bekeley in May 2013.



      Reconstruction Algorithms for Next Generation Imaging: Multi-TieredIterative Phasing for Fluctuation X-ray Scattering and Single-Particle Diffraction

 Jeffrey Donatelli, Mathematics Group, LBNL


With recent advances in imaging technology, we are now able to overcome the
limitations of traditional imaging techniques by performing new imaging
experiments that were previously impossible. One such emerging experimental
technique is fluctuation X-ray scattering (FXS), where one collects a
series of diffraction patterns from multiple particles in solution using an
ultrafast X-ray pulse, which is able to take snapshots below rotational
diffusion times of the particles. The resulting images contain angularly
varying information from which angular correlations can be computed,
yielding several orders of magnitude more information than traditional
solution scattering methods. However, determining molecular structure from
FXS data introduces several challenges, since, in addition to the classical
phase problem, one must also solve a hyper-phase problem to determine the
3D intensity function from the correlation data. In another technique known
as single-particle diffraction (SPD), several diffraction patterns from
individual particles are collected using an ultrabright X-ray beam.
However, the samples are delivered to the beam at unknown orientations and
may also be present in several different conformational states. In order to
reconstruct structural information from SPD, one must determine the
orientation and state for each image, extract an accurate 3D model of the
intensity function from the images, and solve for the missing complex
phases, which are not measured in diffraction images.

In this talk, we present the multi-tiered iterative phasing (M-TIP)
algorithm for determining molecular structure from FXS and SPD data. This
algorithm breaks up the associated reconstruction problems into a set of
simpler subproblems that can be efficiently solved by applying a series of
projection operators. These operators are combined in an iterative
framework which is able to simultaneously determine missing parameters, the
3D intensity function, the complex phases, and the underlying structure
from the data. In particular, this approach is able to leverage prior
knowledge about the structural model, such as finite size or symmetry, to
obtain a reconstruction from very limited data with excellent global
convergence properties and high computational efficiency. We show results
from applying M-TIP to determine molecular structure from both simulated
data and experimental data collected at the Linac Coherent Light Source

Kumar Aatish, 2PM, Monday, April 18, 2016.

Kumar Aatish is a software engineer at ArrayFire specializing in GPGPU technologies such as CUDA and OpenCL. He received his Bachelors in Computer Science from Birla Institute of Technology and Science in 2009 where he got his first taste of high performance computing while implementing PDE solvers on the IBM Cell Broadband Engine. After spending two years volunteering for Prakash Children's Foundation, he joined a Masters program in Computational Science Mathematics and Engineering at University of California, San Diego in 2012. In the summer of 2013 he interned at Berkeley Labs where he worked on CUDA accelerated Ptychography imaging algorithms at Advanced Light Source. After graduating from his graduate program in 2014 he joined ArrayFire and has since worked on a number of projects involving graph analytics on the GPU and Non Uniform 3 Dimensional Fast Fourier Transform. His job involves acceleration of current algorithms or creating parallel alternatives which are performant on the GPU.



      Non Uniform 3 Dimensional Fast Fourier Transform on Multi GPUs

 Kumar Aatish, ArrayFire


While FFT solves the Fourier Transform in O(N log N), it relies on the fact that the input is sampled at equidistant intervals. Non Uniform Fast Fourier transform seeks to overcome this restriction as analysis of irregular data is needed by many scientific disciplines. This talk deals with the implementation specifics of solving the inversion of NFFT using the Conjugate Gradient Residual Minimization method on multiple CUDA capable GPUs, that is computation of Fourier coefficients from given samples at irregular data points in a volume.

K. Aditya Mohan, 3:30PM, Mar 2, 2016, 50B-4205
  • K. Aditya Mohan is currently a PhD candidate at the department of electrical and computer engineering, Purdue University, IN. He received his B.Tech. degree in electronics and communication engineering from National Institute of Technology Karnataka, Surathkal, India in 2010 and M.S. in electrical and computer engineering from Purdue University, IN, in 2014. His PhD thesis is on the design and implementation of model-based iterative reconstruction (MBIR) algorithms for X-ray absorption and phase contrast tomography. He developed a method called TIMBIR for time-space tomographic reconstructions that has been shown to achieve up to 32x gain in temporal resolution without any new investment in sensor technology. His research on 4D imaging of dendritic growth using TIMBIR was recognized by APS as one of the outstanding recent results from their beamlines and was also selected to appear among the science highlights in the 2015 APS annual report of Argonne National Lab. His research interests are in inverse problems, statistical signal processing, computational imaging, and computed tomography.



      Model-Based Iterative Reconstruction Algorithms for X-ray Absorption and Phase Contrast Tomography

 K. Aditya Mohan

Department of Electrical and Computer Engineering

Purdue University


X-ray absorption and phase contrast tomography are widely used for 3D and 4D characterization of material and biological samples. The conventional approach to reconstruction makes use of analytical inversion methods that make various limiting assumptions about the object and the measurement physics. Furthermore, they are also sensitive to noise and limited data. For instance, the analytical filtered back projection algorithm used in X-ray tomography requires Nyquist sampling of projection data and an unchanging sample. In phase contrast tomography, the analytical phase retrieval algorithms make the near-field assumption for diffraction that limits the spatial resolution and image contrast.

In this talk, I will present model-based iterative reconstruction algorithms for X-ray absorption and phase contrast tomography that makes efficient use of all the available data and is robust to noise. I will present a time interlaced model-based iterative reconstruction (TIMBIR) method, which can significantly, improve the temporal resolution of time-space reconstructions. TIMBIR is a synergistic combination of two innovations. The first innovation, interlaced view sampling, is a novel approach to data acquisition, which distributes the view angles more evenly in time. The second innovation is a 4D model based iterative reconstruction algorithm (MBIR), which can produce time resolved volumetric reconstructions of the sample from the interlaced views. I will also present a model-based iterative reconstruction (MBIR) algorithm for X-ray phase contrast tomography called complex refractive index tomographic iterative reconstruction (CRITIR). CRITIR is based on a non-linear physics based model for X-ray propagation and a prior model for the complex refractive index of the object being imaged. Unlike conventional methods, CRITIR is designed to work within and beyond the near-field diffraction region.

Charles Bowman, 3:30PM, Feb 18, 2016, 59-4102
  • Charles A. Bouman is the Showalter Professor of Electrical and Computer Engineering and Biomedical Engineering at Purdue University. He received his B.S.E.E. degree from the University of Pennsylvania, M.S. degree from the University of California at Berkeley, and Ph.D. from Princeton University in 1989.

    Professor Bouman’s research is in statistical signal and image processing in applications ranging from medical to scientific and consumer imaging. His research resulted in the first commercial model-based iterative reconstruction (MBIR) system for medical X-ray computed tomography (CT), and he is co-inventor on over 47 issued patents that have been licensed and used in millions of consumer imaging products. Prof. Bouman is member of the National Academy of Inventors, a Fellow of the IEEE, AIMBE, IS&T, and SPIE. He has served as the IEEE Signal Processing Society’s Vice President of Technical Directions, Editor-in-Chief of the IEEE Transactions on Image Processing, Vice President of Publications for the IS&T Society and was the 2014 recipient of the Electronic Imaging Scientist of the Year award.



      Super-Voxel ICD: Mapping Model-Based Reconstruction to High

                             Performance Computers

                                           Charles Bowman

          Showalter Professor of Electrical and Computer Engineering and

                               Biomedical EngineeringPurdue University


Computed Tomography (CT) Image Reconstruction is an important technique used in a wide range of applications, ranging from explosive detection, medical imaging to scientific imaging. Among available reconstruction methods, Model Based Iterative Reconstruction (MBIR) produces higher quality images and allows for the use of more general CT scanner geometries than is possible with more commonly used methods. The high computational cost of MBIR, however, often makes it impractical in applications for which it would otherwise be ideal. In this talk, we describe a new MBIR implementation that significantly reduces the computational cost of MBIR while retaining its benefits. It describes a novel organization of the scanner data into super-voxels (SV) that, combined with a super-voxel buffer (SVB), dramatically increase locality and prefetching, enable parallelism across SVs and lead to an average speedup of 187 on 20 cores.

Nikolay Malitsky  9 AM, Feb 8, 2016, 59-4102
  • Nikolay Malitsky is a senior architect on the National Light Source Project II. He is currently working on the integration of image processing algorithms with HPC and Big Data technologies to address the new challenges of data-intensive science. Before NSLS-II, Nikolay was involved in several accelerator projects, designing and building large-scale high-performance computational applications and three-tier model-based control systems starting with a virtual accelerator of the Superconducting Super Collider (SSC). This experience was generalized into the Unified Accelerator Libraries (UAL) framework which addressed composite modeling studies, encompassing high-order maps, spin dynamics, space charge effects, dynamic processes, and multiple extensions. Nikolay holds a MS in Experimental Nuclear Physics from Leningrad Polytechnic Institute.

Daan Pelt 9 AM, Feb 5, 2016, 59-4102
  •   Daniël M. Pelt received the M.Sc. degree in mathematics from the University of Utrecht, The Netherlands, in 2010. He is currently pursuing the Ph.D. degree at Centrum Wiskunde en Informatica, Amsterdam, The Netherlands, focusing on filter-based reconstruction algorithms for limited-data tomography problems. He is also involved in the development of the ASTRA toolbox, an open-source toolbox for tomographic reconstruction. He will give a CAMERA-invited talk on Feb. 5, 2016 at 9AM, Building 50F-1647.



      Recent advances in filter-based tomographic reconstruction methods

                   Daan Pelt

          Centrum Wiskunde en Informatica, Amsterdam, The Netherlands


Various advanced tomographic reconstruction methods are available
to improve reconstruction quality in the case of incomplete or noisy
projection data. Most of these methods, however, are computationally
expensive and difficult to implement, and are therefore not used routinely
at experimental facilities. Filtered backprojection, on the other hand, is
fast, easy to implement, robust, and very popular, but its reconstruction
quality degrades if the data has a low signal-to-noise ratio, or if only a
small number of projections are available.
  We have recently developed a range of new reconstruction methods that
improve the quality of filtered backprojection by changing the convolution
filter. Different approaches of changing the filter can be used, each with
their own advantages and disadvantages. The reconstruction quality of these new methods is often on par with slower, more advanced reconstruction methods, but because the methods are based on filtered backprojection, existing efficient implementations can be used at experimental facilities to implement them with minimal effort.


Doga Gursoy: 9 AM, Feb 4, 2016, 59-4102
  • Doga Gursoy joined Argonne in 2013 as a postdoc and since 2015 he has been working as an assistant computational scientist at the X-ray Science Division of Advanced Photon Source. He received the B.Sc. and M.Sc. degrees in electrical engineering from Middle East Technical University, in 2004 and 2007, and the Ph.D degree from Graz University of Technology in electrical engineering in 2010. His research focus has been primarily on the modeling and algorithmic aspects of computational imaging and inverse problems with specific applications in bio and materials sciences. He has a broad interest in modeling of forward and inverse photon transport processes and numerical methods for solving large-scale parameter estimation problems. He will give a CAMERA-invited talk on Feb. 4, 2016 at 9AM, Building 50F-1647.



      How should we acquire and interpret data in x-ray tomography?

                   Doga Gursoy, X-ray Science Division

          Advanced Photon Source, Argonne National Laboratory


Tomography is a broad name for describing the process of reconstructing the interior of an object from multiple measurements taken from the outside. In this talk, after briefly explaining the data formation process of tomography and the mathematical formalism behind it, I'll mainly focus on how we can change the way we collect data to obtain the most useful information from our samples under limited experimental conditions constrained by time and radiation dose. I'll compare the traditional and the contemporary approaches for various tomographic reconstruction methods, and discuss how these new approaches can be adopted for imaging of dynamical systems where the sample can evolve in time.

Zhang Jiang: 10 AM, Jan 25, 2016, 50F-1647
  • Dr. Zhang Jiang is currently a beamline scientist at the Advanced Photon Source (APS), Argonne National Laboratory. He received a Ph.D. in physics from University of California, San Diego in 2007. Then he moved to Argonne and did his postdoc in the Time-Resolved Research group at APS. He then became a physicist and a beamline scientist at Sector 8-ID, where he is responsible for the operation and management of the GISAXS beamline, and partially the XPCS beamlineHe will give a CAMERA-invited talk on Jan, 25, 2016 at 11AM, Building 50F-1647.



      Digging Deeper Into Grazing-incidence X-ray Scattering

                   Zhang Jiang, X-ray Science Division

          Advanced Photon Source, Argonne National Laboratory


Grazing-incidence X-ray Scattering (GIXS) can provide invaluable data to reveal structure of surfaces, interfaces and thin films. Here, a deeper understanding of GIXS will be discussed beyond how GIXS is routinely analyzed nowadays by the community. The general perception has been that GIXS data yields mostly the in-plane structure and its correlation in planar and thin film samples, for example, defects and disordering in 2D nanoparticle superlattices. To obtain the structure information along the 3rd dimension, one can take advantage of the interference of the scattering from parallel surfaces of a thin film to enhance or reduce the scatterings from certain depths of the film (so called X-ray standing wave or waveguide effect). In a broader view, GIXS, as a surface probe, can be readily adapted and combined with other techniques for versatile experimental conditions to study both structures and dynamics at surfaces and interfaces. This imposes a challenge in understanding the scattering mechanism of GIXS in different situations in order for correct data analysis.

Markus Weigand: 11AM, Jan 20, 2016, 2-400F
  • Markus Weigand is the group leader for X-Ray microscopy at the Max Plank Institute for intelligent systems (Stuttgart), primarily bsaed in Berlin at BESSY. He will give a CAMERA-invited talk on Jan, 20, 2016 at 11AM, Building 2-400F.



 The Max Planck Institute for Intelligent System (formerly Metals Research) is operating a STXM as a dedicated undulator beamline endstation as the BESSY II Synchrotron in Berlin with main focus on time resolved and surface sensitive microscopy on magnetic samples. We will present an overview over the capabilities of the instruments and ongoing upgrades in the fields of cryogenic sample stages, >10 GHz time resolved microcopy and ptychographic imaging using a 1000fps in-vacuum soft X-ray camera and review the highlights of the first 5 years of user operation. The second focus of the seminar will be the challenges and possibilities of pump-and-probe imaging using STXM, covering all steps from efficient single photon detection up to the evaluation of the evaluation and optimization of the synchrotron bunch timing.

Roarke Horstmeyer: 2PM, Dec 17, 2015, LBL 2-100B-CR(45-50)
  • Roarke Horstmeyer is a recent PhD graduate from Caltech’s electrical engineering department, who mostly works with optics and algorithms. He will give a CAMERA-invited talk on Dec 17, 2015  at 2PM , Building 2-100B-CR (45-50)



  Optical aberrations limit the size of current microscope images
to tens of megapixels. This talk will present a method to boost the
resolving power of microscopes to one gigapixel, using a technique termed
Fourier ptychography. No moving parts or precision controls are needed for
this resolution enhancement. The only required hardware is a standard
digital microscope, which we outfit with an array of LEDs. A phase
retrieval-based optimization algorithm does the rest of the work. Example
applications of our new microscope include full-slide imaging for digital
pathology, achieving sub-wavelength resolution without using oil immersion,
and creating complex 3D reconstructions of thick biological specimens by
borrowing tools from diffraction tomography.