arXiv subjects

Juergen Popp

Publications and source records attributed to Juergen Popp.

4 recordsLinked to original sources

arXiv2026

iPINN for Broadband CARS Phase Retrieval: A Framework for Function Approximation and Inverse Modeling Problems in Nonlinear Spectroscopy

Phase retrieval in broadband coherent anti-Stokes Raman spectroscopy (BCARS) is an ill-posed inverse problem. The Raman-like signal is encoded in the imaginary part of the resonant susceptibility, which mixes coherently with a non-resonant background (NRB) that varies across acquisitions. We introduce an inverse physics-informed neural network (iPINN) that predicts Lorentzian peak parameters from raw BCARS spectra and reconstructs the resonant susceptibility through a differentiable analytical forward model. A transformer encoder assigns spectral features to 24 learnable peak slots, and a multi-view consistency loss enforces invariance across NRB pattern, NRB strength, and noise. Unlike direct spectral regression approaches, the method retains accuracy under varying acquisition conditions. On a public benchmark, iPINN achieves the lowest error among the tested baselines (MAE 0.016 vs. next-best 0.046). On 28 zero-shot test spectra acquired across seven solvents and four focal positions, accuracy is depth-invariant in five of seven solvents. These results show that inverse parametric prediction with a differentiable physical decoder supports robust phase retrieval across measurement conditions.

cs.LG↗

arXiv2026

Free-electron laser-based extended wide-field mid-infrared photothermal imaging for biomedical and microplastic analysis

Wide-field mid-infrared photothermal (MIP) imaging offers rapid labelfree chemical contrast for biomedical and polymer analysis. However, its field of view (FOV) is limited by the pulse intensity of conventional infrared lasers. Here, we present a wide-field MIP microscope that uses a high-power free-electron laser (FEL) rather than a quantum cascade laser (QCL) as the pump source to achieve a substantially larger FOV. Both implementations use counter-propagating beam paths with a 450 nm LED as the probe source and a CMOS camera that records images using a virtual lock-in detection scheme. QCL nanojoule pulse energies enables FOV of around 45 micrometers for widefield MIP imaging with a sub-micrometer resolution for polystyrene beads, Mycobacterium tuberculosis infected fixed tissues, and laryngeal cancer cryosections. IR spectra in the range of 1000-1800 wavenumbers can be reconstructed by tuning the QCL. FEL pulse energies of up to microjoules expand the FOV by a factor of nearly 20 as demonstrated by wide-field MIP imaging of polystyrene beads, single cells, and murine brain tissue. We discuss current challenges and further improvements to implement high-power IR lasers for wide-field MIP imaging with even larger FOVs in the context of biomedical research and diagnostics.

physics.optics↗

arXiv2025

LEO: An Open-Source Platform for Linking OMERO with Lab Notebooks and Heterogeneous Metadata Sources

In the interdisciplinary field of microscopy research, managing and integrating large volumes of data stored across disparate platforms remains a major challenge. Data types such as bioimages, experimental records, and spectral information are often maintained in separate repositories, each following different management standards. However, linking these data sources across the research lifecycle is essential to align with the FAIR principles of data management: Findability, Accessibility, Interoperability, and Reusability. Despite this need, there is a notable lack of tools capable of effectively integrating and linking data from heterogeneous sources. To address this gap, we present LEO (Linking Electronic Lab Notebooks with OMERO), a web-based platform designed to create and manage links between distributed data systems. LEO was initially developed to link objects between Electronic Lab Notebooks (ELNs) and OMERO, but its functionality has since been extended through a plugin-based architecture, allowing the integration of additional data sources. This extensibility makes LEO a scalable and flexible solution for a wide range of microscopy research workflows.

cs.CE↗

arXiv2022

RAMANMETRIX: a delightful way to analyze Raman spectra

Although Raman spectroscopy is widely used for the investigation of biomedical samples and has a high potential for use in clinical applications, it is not common in clinical routines. One of the factors that obstruct the integration of Raman spectroscopic tools into clinical routines is the complexity of the data processing workflow. Software tools that simplify spectroscopic data handling may facilitate such integration by familiarizing clinical experts with the advantages of Raman spectroscopy. Here, RAMANMETRIX is introduced as a user-friendly software with an intuitive web-based graphical user interface (GUI) that incorporates a complete workflow for chemometric analysis of Raman spectra, from raw data pretreatment to a robust validation of machine learning models. The software can be used both for model training and for the application of the pretrained models onto new data sets. Users have full control of the parameters during model training, but the testing data flow is frozen and does not require additional user input. RAMANMETRIX is available in two versions: as standalone software and web application. Due to the modern software architecture, the computational backend part can be executed separately from the GUI and accessed through an application programming interface (API) for applying a preconstructed model to the measured data. This opens up possibilities for using the software as a data processing backend for the measurement devices in real-time. The models preconstructed by more experienced users can be exported and reused for easy one-click data preprocessing and prediction, which requires minimal interaction between the user and the software. The results of such prediction and graphical outputs of the different data processing steps can be exported and saved.

physics.data-an↗