6 citations · 16 across the 12 of their papers we have counts for
13 papers
Image Priors for Single-Shot Coded Diffraction Phase Retrieval
Zhiyuan Hu, YoonSeok Baek, Sylvain Gigan +2
Phase retrieval recovers complex-valued objects from intensity-only measurements. In its classical Fourier form, reconstruction suffers from twin-image stagnation. Coded diffractio…
Structured Random Models for Phase Retrieval with Optical Diffusers
Zhiyuan Hu, Fakhriyya Mammadova, Julián Tachella +2
Phase retrieval is a nonlinear inverse problem that arises in a wide range of imaging modalities, from electron microscopy to Fourier ptychography. In particular, the reconstructio…
A global inverse-problem approach to quantitative photo-switching optoacoustic mesoscopy
Yan Liu, Jonathan Chuah, Michael Unser +1
In this paper, we propose a global framework that includes a detailed model of the photo-switching and acoustic processes for photo-switching optoacoustic mesoscopy, based on the u…
Breaking the Weak Recovery Limit in Random Phase Retrieval with Learned Regularizers
Stanislas Ducotterd, Zhiyuan Hu, Michael Unser +1
We seek to recover an unknown signal from nonlinear amplitude-only measurements, a challenging inverse problem. Strong theoretical guarantees have been established for idealized ra…
Revisiting Deep Information Propagation: Fractal Frontier and Finite-size Effects
Giuseppe Alessio D'Inverno, Zhiyuan Hu, Leo Davy +3
Information propagation characterizes how input correlations evolve across layers in deep neural networks. This framework has been well studied using mean-field theory, which assum…
Sensitivity-Aware Density Estimation in Multiple Dimensions
Aleix Boquet-Pujadas, Pol del Aguila Pla, Michael Unser
We formulate an optimization problem to estimate probability densities in the context of multidimensional problems that are sampled with uneven probability. It considers detector s…
Revisiting PSF models: unifying framework and high-performance implementation
Yan Liu, Vasiliki Stergiopoulou, Jonathan Chuah +5
Localization microscopy often relies on detailed models of point spread functions. For applications such as deconvolution or PSF engineering, accurate models for light propagation…
Perturbative Fourier Ptychographic Microscopy for Fast Quantitative Phase Imaging
Martin Zach, Kuan-Chen Shen, Ruiming Cao +3
In computational phase imaging with a microscope equipped with an array of light emitting diodes as illumination unit, conventional Fourier ptychographic microscopy achieves high r…
Point-Spread-Function Engineering in MINFLUX: Optimality of Donut and Half-Moon Excitation Patterns
Yan Liu, Jonathan Dong, Juan Augusto Maya +2
Localization microscopy enables imaging with resolutions that surpass the conventional optical diffraction limit. Notably, the MINFLUX method achieves super-resolution by shaping t…
Structured Random Model for Fast and Robust Phase Retrieval
Zhiyuan Hu, Julián Tachella, Michael Unser +1
Phase retrieval, a nonlinear problem prevalent in imaging applications, has been extensively studied using random models, some of which with i.i.d. sensing matrix components. While…
Model-based temporal unmixing towards quantitative photo-switching optoacoustic tomography
Yan Liu, Jonathan Chuah, Yishu Huang +3
Optoacoustic (OA) imaging combined with reversibly photoswitchable proteins has emerged as a promising technology for the high-sensitivity and multiplexed imaging of cells in live…
Mechanical Artifacts in Optical Projection Tomography: Classification and Automatic Calibration
Yan Liu, Jonathan Dong, Thanh-An Pham +2
Optical projection tomography (OPT) is a powerful tool for biomedical studies. It achieves 3D visualization of mesoscopic biological samples with high spatial resolution using conv…
Mechanical Artifacts in Optical Projection Tomography: Classification and Automatic Calibration
Yan Liu, Jonathan Dong, Thanh-an Pham +2
Optical projection tomography (OPT) is a powerful tool for biomedical studies. It achieves 3D visualization of mesoscopic biological samples with high spatial resolution using conv…