arXiv subjects

Baptiste Nicolet

Publications and source records attributed to Baptiste Nicolet.

3 recordsLinked to original sources

arXiv2025

Physically-Based Inverse Rendering Framework for PET Image Reconstruction

Differentiable rendering has been widely adopted in computer graphics as a powerful approach to inverse problems, enabling efficient gradient-based optimization by differentiating the image formation process with respect to millions of scene parameters. Inspired by this paradigm, we propose a physically-based inverse rendering (IR) framework, the first ever platform for PET image reconstruction using Dr.Jit, for PET image reconstruction. Our method integrates Monte Carlo sampling with an analytical projector in the forward rendering process to accurately model photon transport and physical process in the PET system. The emission image is iteratively optimized using voxel-wise gradients obtained via automatic differentiation, eliminating the need for manually derived update equations. The proposed framework was evaluated using both phantom studies and clinical brain PET data acquired from a Siemens Biograph mCT scanner. Implementing the Maximum Likelihood Expectation Maximization (MLEM) algorithm across both the CASToR toolkit and our IR framework, the IR reconstruction achieved a higher signal-to-noise ratio (SNR) and improved image quality compared to CASToR reconstructions. In clinical evaluation compared with the Siemens Biograph mCT platform, the IR reconstruction yielded higher hippocampal standardized uptake value ratios (SUVR) and gray-to-white matter ratios (GWR), indicating enhanced tissue contrast and the potential for more accurate tau localization and Braak staging in Alzheimer's disease assessment. The proposed IR framework offers a physically interpretable and extensible platform for high-fidelity PET image reconstruction, demonstrating strong performance in both phantom and real-world scenarios.

physics.med-ph↗

arXiv2025

Overprinting with Tomographic Volumetric Additive Manufacturing

Tomographic Volumetric Additive Manufacturing (TVAM) is a light-based 3D printing technique capable of producing centimeter-scale objects within seconds. A key challenge lies in the calculation of tomographic projection patterns under non-standard conditions, such as the presence of occlusions and materials with diverse optical properties, including varying refractive indices or scattering surfaces. This work demonstrates a broad range of overprinting scenarios, where new structures are directly printed onto or around pre-existing components made from different materials. Our simulations and experimental verifications perform overprinting of absorbing, refracting, reflecting and scattering elements in both round and square vials. All scenarios are optimized with our differentiable, physically based ray-optics approach using the open-source Dr.TVAM framework, delivering high-quality projections for both laser- and LED-based illuminations within minutes and lower-quality projections within seconds, exceeding existing open-source solutions in speed, flexibility, and quality.

physics.optics↗

arXiv2025

Sionna RT: Technical Report

Sionna is an open-source, GPU-accelerated library that, as of version 0.14, incorporates a ray tracer, Sionna RT, for simulating radio wave propagation. A unique feature of Sionna RT is differentiability, enabling the calculation of gradients for the channel impulse responses (CIRs), radio maps, and other related metrics with respect to system and environmental parameters, such as material properties, antenna patterns, and array geometries. The release of Sionna 1.0 provided a complete overhaul of the ray tracer, significantly improving its speed, memory efficiency, and extensibility. This document details the algorithms employed by Sionna RT to simulate radio wave propagation efficiently, while also addressing their current limitations. Given that the computation of CIRs and radio maps requires distinct algorithms, these are detailed in separate sections. For CIRs, Sionna RT integrates shooting and bouncing of rays (SBR) with the image method and uses a hashing-based mechanism to efficiently eliminate duplicate paths. Radio maps are computed using a purely SBR-based approach for the non-diffracted component, complemented by a stage for diffracted paths.

cs.IT↗