arXiv subjects

Jan Becker

Publications and source records attributed to Jan Becker.

3 recordsLinked to original sources

arXiv2025

Interferometric optical mass measurement in the low-reference regime

The precise optical, label-free, measurement of mass at the nanoscale has been significantly advanced by techniques based on interferometric scattering, such as mass photometry (MP). These methods exploit the interference between a scattered and reference field to achieve a high signal-to-noise ratio (SNR) for weakly scattering objects (e.g. proteins) and are currently limited to masses bigger than 40 kDa. Standard MP employs a mask that attenuates the reference field, allowing for the increase in illumination power without saturation of the detector. In this theoretical study, we examine how the SNR evolves when extending reference attenuation beyond conventional levels: entering the low-reference regime. Our simplified model finds that a substantial SNR enhancement can be achieved when the magnitude of reference matches that of the scattered field and investigate refractive index tuning as a potential method to reach the required attenuation in practice. The accomplishable SNR improvement can be tailored to a given mass region, i.e. allowing the detection of masses smaller than 40 kDa.

physics.optics↗

arXiv2020

StyPath: Style-Transfer Data Augmentation For Robust Histology Image Classification

The classification of Antibody Mediated Rejection (AMR) in kidney transplant remains challenging even for experienced nephropathologists; this is partly because histological tissue stain analysis is often characterized by low inter-observer agreement and poor reproducibility. One of the implicated causes for inter-observer disagreement is the variability of tissue stain quality between (and within) pathology labs, coupled with the gradual fading of archival sections. Variations in stain colors and intensities can make tissue evaluation difficult for pathologists, ultimately affecting their ability to describe relevant morphological features. Being able to accurately predict the AMR status based on kidney histology images is crucial for improving patient treatment and care. We propose a novel pipeline to build robust deep neural networks for AMR classification based on StyPath, a histological data augmentation technique that leverages a light weight style-transfer algorithm as a means to reduce sample-specific bias. Each image was generated in 1.84 +- 0.03 seconds using a single GTX TITAN V gpu and pytorch, making it faster than other popular histological data augmentation techniques. We evaluated our model using a Monte Carlo (MC) estimate of Bayesian performance and generate an epistemic measure of uncertainty to compare both the baseline and StyPath augmented models. We also generated Grad-CAM representations of the results which were assessed by an experienced nephropathologist; we used this qualitative analysis to elucidate on the assumptions being made by each model. Our results imply that our style-transfer augmentation technique improves histological classification performance (reducing error from 14.8% to 11.5%) and generalization ability.

cs.CV↗

arXiv2018

Better than a lens -- Increasing the signal-to-noise ratio through pupil splitting

Lenses are designed to fulfill Fermats principle such that all light interferes constructively in its focus, guaranteeing its maximum concentration. It can be shown that imaging via an unmodified full pupil yields the maximum transfer strength for all spatial frequencies transferable by the system. Seemingly also the signal-to-noise ratio (SNR) is optimal. The achievable SNR at a given photon budget is critical especially if that budget is strictly limited as in the case of fluorescence microscopy. In this work we propose a general method which achieves a better SNR for high spatial frequency information of an optical imaging system, without the need to capture more photons. This is achieved by splitting the pupil of an incoherent imaging system such that two (or more) sub-images are simultaneously acquired and computationally recombined. We compare the theoretical performance of split pupil imaging to the non-split scenario and implement the splitting using a tilted elliptical mirror placed at the back-focal-plane (BFP) of a fluorescence widefield microscope.

physics.optics↗