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Open Access Publications from the University of California

Scholarly Works (4 results)

  • Thesis
  • Peer Reviewed
UC Berkeley Electronic Theses and Dissertations (2018)

4D phase space descriptions of light capture wave-optical and angular information, enabling digitally refocusing, 3D reconstructions and aberration removal. The wave-optical theory includes diffraction and interference effects, making phase space applicable to scales near the wavelength of light (e.g. in microscopy); however, at the cost of making phase space functions more complicated than their ray optics counterparts (light fields). In this thesis, we aim at bridging the gap between the abstract high-dimensional phase space and actual experiments upon which the reconstruction of unknown objects relies. We achieve the aim by 1) providing practical methods of measuring phase-space functions with good resolution in all 4D and 2) developing phase-space theories that we use to computationally mitigate scattering in experimental situations. We extend phase-space measurement schemes from from lenslet arrays to a scanning-based coded aperture method in order to improve information throughput. Theory and experiment for designed coded apertures is proposed that can efficiently capture the entire 4D phase space. Next, we develop a phase-space theory for imaging through scattering and apply it to experimentally imaging point sources through scattering and tracking neural activity in a scattering environment, such as mouse brain tissue. The method utilizes the dimension mismatch between 3D object and 4D phase-space measurements, along with a sparsity prior, to ensure robustness and allow 3D localization of point sources relatively deep into scattering tissue. We develop theory and verify the mathematical phase-space scattering operator, then study how light interacts with scatterers and propose a fast wave-equation solver. This method uses an accelerated gradient descent solver and expands the solution to the wave equation as a series of the gradient solver updates. The method outperforms the first Born approximation and the Rytov approximation in predicting the scattered field as well as in reconstructing the scatterer distributions.

    Cover page: Optical Phase Space Measurements and Applications to 3D Imaging and Light Scattering
    • Article
    • Peer Reviewed
    UC Berkeley Previously Published Works (2016)
    Understanding the mechanisms of perception, cognition, and behavior requires instruments that are capable of recording and controlling the electrical activity of many neurons simultaneously and at high speeds. All-optical approaches are particularly promising since they are minimally invasive and potentially scalable to experiments interrogating thousands or millions of neurons. Conventional light-field microscopy provides a single-shot 3D fluorescence capture method with good light efficiency and fast speed, but suffers from low spatial resolution and significant image degradation due to scattering in deep layers of brain tissue. Here, we propose a new compressive light-field microscopy method to address both problems, offering a path toward measurement of individual neuron activity across large volumes of tissue. The technique relies on spatial and temporal sparsity of fluorescence signals, allowing one to identify and localize each neuron in a 3D volume, with scattering and aberration effects naturally included and without ever reconstructing a volume image. Experimental results on live zebrafish track the activity of an estimated 800+ neural structures at 100 Hz sampling rate.
      • Article
      • Peer Reviewed
      UC Berkeley Previously Published Works (2015)
      We demonstrate the use of phase-space imaging for 3D localization of multiple point sources inside scattering material. The effect of scattering is to spread angular (spatial frequency) information, which can be measured by phase space imaging. We derive a multi-slice forward model for homogenous volumetric scattering, then develop a reconstruction algorithm that exploits sparsity in order to further constrain the problem. By using 4D measurements for 3D reconstruction, the dimensionality mismatch provides significant robustness to multiple scattering, with either static or dynamic diffusers. Experimentally, our high-resolution 4D phase-space data is collected by a spectrogram setup, with results successfully recovering the 3D positions of multiple LEDs embedded in turbid scattering media.
        Cover page: 3D imaging in volumetric scattering media using phase-space measurements
        • Article
        • Peer Reviewed
        UC Berkeley Previously Published Works (2018)
        Linear operators used in iterative methods like conjugate gradient have typically been implemented either as ''matrix-driven'' subroutines backed by explicit sparse or dense matrices, or as ''matrix-free'' subroutines that implement specific linear operations directly (e.g. FFTs). The matrix-driven approach is generally more portable because it can target widely-Available BLAS libraries, but it can be inefficient in terms of time and space complexity. In contrast, the matrix-free approach is more performant because it leverages structure in operations, but it requires each operator be re-implemented on each new platform. To increase performance and portability, we propose a hybrid approach that represents linear operators as expression trees. Leaf nodes in the tree are either matrix-free or matrix-driven operators, and interior nodes represent mathematical compositions (sums, products, transposes) or structural compositions (stacks, block diagonals, etc.) of the leaf operators. This representation enables expert-guided reordering and fusion transformations that can improve performance or reduce memory pressure. We implement our approach in a domain-specific language called Indigo. We assess Indigo on image reconstruction problems arising in four application areas: magnetic resonance imaging, ptychography, magnetic particle imaging, and fluorescent microscopy. We give performance results from vendor BLAS libraries, and we introduce specializations to Sparse BLAS routines that achieve near-Roofline performance on multi-core, many-core, and GPU systems.
          Cover page: Indigo: A Domain-Specific Language for Fast, Portable Image Reconstruction
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