Publications by Joowon Lim | EPFL Graph Search

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Maxwell's equations govern light propagation and its interaction with matter. Therefore, the solution of Maxwell's equations using computational electromagnetic simulations plays a critical role in understanding light-matter interaction and designing optic ...

Optical diffraction tomography (ODT) provides us 3D refractive index (RI) distributions of transparent samples. Since RI values differ across different materials, they serve as endogenous contrasts. It, therefore, enables us to image without pre-processing ...

Optical diffraction tomography (ODT) can be described using the scattering process through an inhomogeneous media. An inherent nonlinearity exists relating the scattering medium and the scattered field due to multiple scattering. Multiple scattering is oft ...

We accurately reconstruct three-dimensional (3-D) refractive index (RI) distributions from highly ill-posed two-dimensional (2-D) measurements using a deep neural network (DNN). Strong distortions are introduced on reconstructions obtained by the Wolf tran ...

Computer generated optical volume elements have been investigated for information storage, spectral filtering, and imaging applications. Advancements in additive manufacturing (3D printing) allow the fabrication of multilayered diffractive volume elements ...

A new approach to optical diffraction tomography (ODT) based on intensity measurements is presented. By applying the Wolf transform directly to intensity measurements, we observed unexpected behavior in the 3D reconstruction of the sample. Such a reconstru ...

The accurate identification of the three-dimensional quantitative shape of a cell nucleus is now possible without fluorescent staining by applying computational segmentation to refractive index tomograms recorded in the flow cytometry mode. ...

In recent years, researchers have obtained impressive reconstructions of the refractive index (RI) of biological objects through the combined use of advanced physics (nonlinear forward model) and regularization. Here, we propose an adaptation of these tech ...

A broad class of imaging modalities involve the resolution of an inverse-scattering problem. Among them, three-dimensional optical diffraction tomography (ODT) comes with its own challenges. These include a limited range of views, a large size of the sampl ...

Polarization of light has been widely used as a contrast mechanism in two-dimensional (2D) microscopy and also in some three-dimensional (3D) imaging modalities. In this paper, we report the 3D tomographic reconstruction of the refractive index (RI) tensor ...

Identifying intracellular organelles within the 3D label-free tomograms of cells’ refractive indexes recorded in flow cytometry is challenging. Here we present a method for the 3D statistical segmentation of nuclei and vacuoles in flowing cells. ...

Joowon Lim

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MaxwellNet: Physics-driven deep neural network training based on Maxwell's equations

Learning approaches to high-fidelity optical diffraction tomography

Imaging complex objects using learning tomography

Three-dimensional tomography of red blood cells using deep learning

Computer generated optical volume elements by additive manufacturing

3D reconstruction of weakly scattering objects from 2D intensity-only measurements using the Wolf transform

Stain-free identification of cell nuclei using tomographic phase microscopy in flow cytometry

Phaseless Diffraction Tomography With Regularized Beam Propagation

Three-Dimensional Optical Diffraction Tomography With Lippmann-Schwinger Model

Polarization-sensitive optics diffraction tomography

Computational segmentation of nuclei and vacuoles based on statistical inference for tomographic phase microscopy in flow cytometry

A method for assessing the fidelity of optical diffraction tomography reconstruction methods using structured illumination