activity
20242026
collaborators

11 papers

cs.CV2026

XRF-to-Optical Field-of-View Localization with Vision Language Models

Xiangyu Yin, Tatjana Paunesku, Letonia Copeland-Hardin +7

Registering images acquired with different microscopy modalities is essential for relating complementary measurements of the same specimen. In correlative X-ray fluorescence (XRF)…

cs.CV2026

Acquisition Geometry-Assisted Whole-Group Localization of X-ray Fluorescence Maps in Optical Microscopy Images

Xiangyu Yin, Tatjana Paunesku, Letonia Copeland-Hardin +7

X-ray fluorescence (XRF) microscopy maps elemental distributions, while optical microscopy can provide complementary morphological context. Localizing XRF fields of view (FOVs) in…

physics.med-ph2026

Adaptive Beam Selection for Efficient Scanning Probe Tomography

San Dinh, Zichao Wendy Di, Matt Menickelly

In X-ray tomography, reconstruction quality generally improves with larger numbers of projections. However, more projections increase experiment costs, acquisition time and the rad…

math.NA2026

A Joint Variational Framework for Multimodal X-ray Ptychography and Fluorescence Reconstruction

Chengru Eric Zou, Elle Buser, Zichao Wendy Di +1

Recovering high-resolution structural and compositional information from coherent X-ray measurements involves solving coupled, nonlinear, and ill-posed inverse problems. Ptychograp…

math.NA2026

MAGPIE: Multilevel-Adaptive-Guided Solver for Ptychographic Phase Retrieval

Borong Zhang, Qin Li, Zichao Wendy Di

We introduce MAGPIE (Multilevel-Adaptive-Guided Ptychographic Iterative Engine), a stochastic multigrid solver for the ptychographic phase-retrieval problem. The ptychographic phas…

math.NA2025

Stochastic Multigrid Method for Blind Ptychographic Phase Retrieval

Borong Zhang, Junjing Deng, Yi Jiang +1

We present eMAGPIE (extended Multilevel-Adaptive-Guided Ptychographic Iterative Engine), a stochastic multigrid method for blind ptychographic phase retrieval that jointly recovers…