Senior Member of the Technical Staff
Stephen Anthony's research focuses on developing and applying quantitative imaging and multivariate analysis tools to study the spatio-temporal relationships that underlie key biological processes. A major component of his work is hyperspectral imaging, which when analyzed using multivariate curve resolution (MCR) allows the chemical spectral components and their relative abundance throughout the image to be determined. Activities include both development of and improvement to the data processing algorithms as well as development of new hyperspectral microscopy equipment and techniques. Work in his laboratory is typically multidisciplinary in nature, spanning biology, physics, chemistry, and computer science; frequently algorithms or techniques developed in one field or method can be equally applicable to other seemingly disparate fields. For instance, despite length scales differing by more than 10 orders of magnitude, detection of fluorescent proteins and stars share many similarities.
Bachelor's Degree: Chemistry and Physics, Rice University (1999-2003)
Doctoral Degree: Physical Chemistry, University of Illinois at Urbana-Champaign (2003-2010)
Postdoctoral Fellowship: Sandia National Laboratories (2013-2015)
Stephen Anthony earned his bachelor’s degrees in Chemistry and Physics from Rice University in 2003. While there, Anthony conducted research into the photophysical properties of fullerene derivatives with Bruce Weisman. During his graduate studies at the University of Illinois with Steve Granick, Anthony helped pioneer the field of Janus particles (heterogeneous colloids) as optically accessible probes of translational and rotational microscale dynamics. He also obtained experimental evidence of the limits of validity of the Tube Model, the standard understanding of polymer dynamics. As a crucial component of this research, Anthony developed image analysis algorithms including a particle-tracking algorithm which allows robust tracking of intermittent and low signal-to-noise particle observations. Anthony received a Ph.D. in Physical Chemistry from the University of Illinois in 2010.
While fluorescently stained cells may look nice, unless you can quantify where the different fluorophores are within the cell, all you have is a pretty picture. Particle detection has been a recurrent challenge throughout Anthony's research career, where often existing solutions were insufficient. The nature of the challenge, though, has depended upon what is being imaged. When imaging micron-scale Janus particles, detection of the Janus particles was not an issue, but determining their orientation was. On the other hand, when imaging fluorophores in cells, the number of photons available is limited and low signal-to-noise ratio is a much bigger concern. Research in this area included developing a wavelet-based spot detection algorithm capable of detecting particles in lower signal-to-noise ratio images. Alternatively, simple detection may not be difficult but quantification may be challenging due to the need to distinguish whether an observation corresponds to one particle or multiple particles. In this case, compressive sensing algorithms were adapted to his purposes, demonstrating the capability to resolve a pair of point spread functions (highlighted by the larger, white circle) separated by less than half the Abbe limit.
Single Particle TrackingMoving from spatial information to spatio-temporal dynamics generally requires following of particles (e.g. fluorophores) though time, typically requiring single particle tracking algorithms. Unfortunately, multiple hypothesis tracking is known to be NP-hard, so except for small problems the optimum solution cannot be found, only approximations. Anthony's research has included the development of a quasilinear time N-dimensional particle tracking algorithm. In particular, this algorithm was designed to support arbitrary dimensions beyond standard space and time dimensions. For instance, particle intensity or ellipticity could be incorporated as dimensions.
Hyperspectral and Super-Resolution ImagingFollowing the theme of exploring additional dimensions, some of Anthony's research has focused on multispectral and hyperspectral imaging, adding an additional spectral dimension to the image data. While the resulting image data can extend to 5D data sets (3 spatial dimensions, 1 temporal, and 1 spectral), at its simplest level hyperspectral imaging consists of collecting the intensity at multiple wavelengths for every pixel in a standard 2D image. This ranges from multi-color systems such as Jeri Timlin’s dual-color, video-rate, total internal reflection (TIRF) and stochastic optical reconstruction (STORM) microscope to Michael Sinclair’s hyperspectral confocal microscope which can resolve complete fluorescence spectra. Recent work (along with Jeri Timlin) has focused on combining hyperspectral imaging and super-resolution microscopy, specifically stimulated emission depletion (STED) microscopy, as well as incorporating a second spectral dimension, the excitation spectrum.
Multivariate Curve ResolutionWhen working with higher dimensional data sets like hyperspectral images, our ability as humans to visualize all the data is limited. Moreover, quantitative analysis is much more reliable than subjective human impressions. Therefore, sophisticated multivariate analysis tools are needed to extract the underlying spectral signatures and spatio-temporal distributions. However, while much of Anthony's research has focused on applying multivariate curve resolution (MCR) to hyperspectral images, MCR decompose other signals into components, including gas chromatography-mass spectroscopy (GC-MS).
Selected Book Chapters
Anthony, S.; Carroll-Portillo, A.; Timlin, J., Dynamics and Interactions of Individual Proteins in the Membrane of Living Cells. In Anup K. Singh (Ed.) Single Cell Protein Analysis. Springer 2015, 185-207.
Anthony, S.M.; Kim, M., Janus Particle Localization and Tracking for Studies of Particle Dynamics. In S. Jiang & S. Granick (Eds.), Janus Particle Synthesis, Self-Assembly and Applications. Royal Society of Chemistry 2012, 223-243.