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The Rytov approximation is known in near-infrared spectroscopy including diffuse optical tomography. In diffuse optical tomography, the Rytov approximation often gives better reconstructed images than the Born approximation. Although…

Mathematical Physics · Physics 2023-09-01 Manabu Machida

When the inverse problem of diffuse optical tomography (DOT) is solved with the Born or Rytov approximation, the size of the matrix of the linear inverse problem becomes large if the volume (or area) of the domain in biological tissue used…

Medical Physics · Physics 2021-07-22 Tetsuya Mimura , Yu Jiang , Norikazu Todoroki , Manabu Machida

Optical diffraction tomography relies on solving an inverse scattering problem governed by the wave equation. Classical reconstruction algorithms are based on linear approximations of the forward model (Born or Rytov), which limits their…

Computational Engineering, Finance, and Science · Computer Science 2017-09-01 Emmanuel Soubies , Thanh-An Pham , Michael Unser

Of primary interest in this paper is the numerical approximation of a time dependent fractional, in space, diffusion equation where the domain is assumed to be nonhomogeneous, having different axial diffusion coefficients. This work is…

Numerical Analysis · Mathematics 2026-05-12 T. Catoe , V. J. Ervin

In optical diffraction tomography (ODT), a sample's 3D refractive-index (RI) is often reconstructed after illuminating it from multiple angles, with the assumption that the sample remains static throughout data collection. When the sample…

Optics · Physics 2024-12-13 Jeongsoo Kim , Shwetadwip Chowdhury

In Optical diffraction tomography, the multiply scattered field is a nonlinear function of the refractive index of the object. The Rytov method is a linear approximation of the forward model, and is commonly used to reconstruct images.…

Optical diffraction tomography is an indispensable tool for studying objects in three-dimensions due to its ability to accurately reconstruct scattering objects. Until now this technique has been limited to coherent light because spatial…

Tomography is the three-dimensional reconstruction of an object from images taken at different angles. The term classical tomography is used, when the imaging beam travels in straight lines through the object. This assumption is valid for…

Quantitative Methods · Quantitative Biology 2016-10-10 Paul Müller , Mirjam Schürmann , Jochen Guck

We analyze the inverse scattering series for diffuse waves in random media. In previous work the inverse series was used to develop fast, direct image reconstruction algorithms in optical tomography. Here we characterize the convergence,…

Analysis of PDEs · Mathematics 2009-11-13 Shari Moskow , John C. Schotland

An inverse scattering problem is formulated for reconstructing optical properties of biological tissues. A recursive linearization algorithm is used to solve the inverse scattering problem. We employed the idea of finite element boundary…

Numerical Analysis · Mathematics 2014-04-30 Ying Li

Dynamic inverse problems are challenging to solve due to the need to identify and incorporate appropriate regularization in both space and time. Moreover, the very large scale nature of such problems in practice presents an enormous…

Numerical Analysis · Mathematics 2025-01-23 Toluwani Okunola , Mirjeta Pasha , Misha Kilmer , Melina Freitag

Based on the similarity of paraxial diffraction and dispersion mathematical descriptions, the temporal imaging of optical pulses combines linear dispersive filters and quadratic phase modulations operating as time lenses. We consider…

In this article, we are concerned with the analysis on the numerical reconstruction of the spatial component in the source term of a time-fractional diffusion equation. This ill-posed problem is solved through a stabilized nonlinear…

Numerical Analysis · Mathematics 2020-05-06 Daijun Jiang , Yikan Liu , Dongling Wang

Using diffusion priors to solve inverse problems in imaging have significantly matured over the years. In this chapter, we review the various different approaches that were proposed over the years. We categorize the approaches into the more…

Machine Learning · Computer Science 2025-08-05 Hyungjin Chung , Jeongsol Kim , Jong Chul Ye

We present the first framework to solve linear inverse problems leveraging pre-trained latent diffusion models. Previously proposed algorithms (such as DPS and DDRM) only apply to pixel-space diffusion models. We theoretically analyze our…

Machine Learning · Computer Science 2023-07-04 Litu Rout , Negin Raoof , Giannis Daras , Constantine Caramanis , Alexandros G. Dimakis , Sanjay Shakkottai

In this work we present a novel linear iterative solution to an electromagnetic inverse scattering problem with phaseless data for strongly scattering, lossy media. It is based on an extended Rytov approximation that significantly widens…

Applied Physics · Physics 2022-05-26 Amartansh Dubey , Ross Murch

Diffusion models have recently emerged as powerful generative priors for solving inverse problems. However, training diffusion models in the pixel space are both data-intensive and computationally demanding, which restricts their…

Computer Vision and Pattern Recognition · Computer Science 2024-04-17 Bowen Song , Soo Min Kwon , Zecheng Zhang , Xinyu Hu , Qing Qu , Liyue Shen

In this paper, we study the mathematical imaging problem of optical diffraction tomography (ODT) for the scenario of a microscopic rigid particle rotating in a trap created, for instance, by acoustic or optical forces. Under the influence…

In this paper, we develop a numerical algorithm for an inverse problem on determining fractional orders of time derivatives simultaneously in a coupled subdiffusion system. Following the theoretical uniqueness, we reformulate the order…

Numerical Analysis · Mathematics 2025-08-19 Yikan Liu

In dynamic tomography the object undergoes changes while projections are being acquired sequentially in time. The resulting inconsistent set of projections cannot be used directly to reconstruct an object corresponding to a time instant.…

Image and Video Processing · Electrical Eng. & Systems 2024-01-30 Berk Iskender , Marc L. Klasky , Yoram Bresler
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