paper-with-me

Papers

Differentiable Microscopy Designs an All Optical Phase Retrieval Microscope

2022-03-28 · Kithmini Herath, Udith Haputhanthri, Ramith Hettiarachchi, Hasindu Kariyawasam, Raja N. Ahmad, Azeem Ahmad, Balpreet S. Ahluwalia, Chamira U. S. Edussooriya, Dushan N. Wadduwage

Since the late 16th century, scientists have continuously innovated and developed new microscope types for various applications. Creating a new architecture from the ground up requires substantial scientific expertise and creativity, often spanning years or even decades. In this study, we propose an alternative approach called "Differentiable Microscopy," which introduces a top-down design paradigm for optical microscopes. Using all-optical phase retrieval as an illustrative example, we demonstrate the effectiveness of data-driven microscopy design through $\partial\mu$. Furthermore, we conduct comprehensive comparisons with competing methods, showcasing the consistent superiority of our learned designs across multiple datasets, including biological samples. To substantiate our ideas, we experimentally validate the functionality of one of the learned designs, providing a proof of concept. The proposed differentiable microscopy framework supplements the creative process of designing new optical systems and would perhaps lead to unconventional but better optical designs.

📄 PDF Abstract BibTeX arXiv:2203.14944

Code (0)

등록된 구현이 없습니다.

Tasks

AllRetrieval

Similar Papers 제목 키워드 기반

High resolution functional imaging through Lorentz transmission electron microscopy and differentiable programming

2020-12-07 · Tao Zhou, Mathew Cherukara, Charudatta Phatak

Lorentz transmission electron microscopy is a unique characterization technique that enables the simultaneous imaging of both the microstructure and functional properties of materials at high spatial resolution. The quan…

Retrieval

From Hours to Seconds: Towards 100x Faster Quantitative Phase Imaging via Differentiable Microscopy

2022-05-23 · Udith Haputhanthri, Kithmini Herath, Ramith Hettiarachchi, Hasindu Kariyawasam 외

With applications ranging from metabolomics to histopathology, quantitative phase microscopy (QPM) is a powerful label-free imaging modality. Despite significant advances in fast multiplexed imaging sensors and deep-lear…

SSIM

Sparse deep computer-generated holography for optical microscopy

2021-11-30 · NeurIPS Workshop Deep_Invers 2021 12 · Alex Liu, Yi Xue, Laura Waller

Computer-generated holography (CGH) has broad applications such as direct-view display, virtual and augmented reality, as well as optical microscopy. CGH usually utilizes a spatial light modulator that displays a compute…

OSOG: A Differentiable, Physics-Informed Synthetic Data Engine for Micro-Optical Environments

2026-06-19 · Caio Silva arxiv

Deep learning in computational microscopy is severely constrained by the scarcity of densely annotated datasets. While synthetic data generation has bridged this gap in macroscopic computer vision, traditional graphics e…

Synthetic Data GenerationInverse RenderingObject Detection

Deep learning-based holographic polarization microscopy

2020-07-01 · Tairan Liu, Kevin de Haan, Bijie Bai, Yair Rivenson 외

Polarized light microscopy provides high contrast to birefringent specimen and is widely used as a diagnostic tool in pathology. However, polarization microscopy systems typically operate by analyzing images collected fr…

Deep LearningDiagnosticMedical Diagnosis