arXiv subjects

Aleix Boquet-Pujadas

Publications and source records attributed to Aleix Boquet-Pujadas.

7 recordsLinked to original sources

arXiv2026

Geometry Calibration in Tomography with a Differentiable Ray-Based Model

Geometric misalignments between the nominal and true acquisition parameters in tomography degrade reconstructions. We propose a framework that jointly reconstructs the volume and calibrates the acquisition geometry for arbitrary source--detector configurations. The core of our framework is an x-ray transform operator whose gradients with respect to the acquisition geometry can be efficiently computed with a ray-tracing method of structure and computational complexity similar to those of the forward operator. We represent the volume in a B-spline basis to provide a continuously differentiable model. This results in a better-behaved optimization landscape compared to voxel-based representations. We validate our framework with CT, micro-CT, nano-CT, and positron emission tomography data under a variety of geometric misalignments.

eess.IV↗

arXiv2025

SplineSplat: 3D Ray Tracing for Higher-Quality Tomography

We propose a method to efficiently compute tomographic projections of a 3D volume represented by a linear combination of shifted B-splines. To do so, we propose a ray-tracing algorithm that computes 3D line integrals with arbitrary projection geometries. One of the components of our algorithm is a neural network that computes the contribution of the basis functions efficiently. In our experiments, we consider well-posed cases where the data are sufficient for accurate reconstruction without the need for regularization. We achieve higher reconstruction quality than traditional voxel-based methods.

cs.CV↗

arXiv2025

Sensitivity-Aware Density Estimation in Multiple Dimensions

We formulate an optimization problem to estimate probability densities in the context of multidimensional problems that are sampled with uneven probability. It considers detector sensitivity as an heterogeneous density and takes advantage of the computational speed and flexible boundary conditions offered by splines on a grid. We choose to regularize the Hessian of the spline via the nuclear norm to promote sparsity. As a result, the method is spatially adaptive and stable against the choice of the regularization parameter, which plays the role of the bandwidth. We test our computational pipeline on standard densities and provide software. We also present a new approach to PET rebinning as an application of our framework.

cs.LG↗

arXiv2025

How accurate is mechanobiology? A statistical test of cell force

Mechanobiology is gaining more and more traction as the fundamental role of physical forces in biological function becomes clearer. Forces at the microscale are often measured indirectly using inverse problems such as Traction Force Microscopy because biological experiments are hard to access with physical probes. In contrast with the experimental nature of biology and physics, these measurements do not come with error bars, confidence regions, or p-values. The aim of this manuscript is to publicize this issue and to propose a first step towards a remedy therefor in the form of a general reconstruction framework. We also show that this opens the door to hypothesis testing of seemingly abstract experimental questions.

physics.bio-ph↗

arXiv2024

Inverse Measurements in Active Nematics

We present a framework to take new measurements in nematic systems that contain active elements such as molecular motors. Spatio-temporal fields of stress, traction, velocity, pressure, and forces are estimated jointly from microscopy images alone. Our inverse-problem approach ensures that these fields comply with physical laws and are accurate at system boundaries. Our novel measurements in active biological materials provide new insight for the design of boundary-aware nematic systems. The shear stress at the wall unveils a correlation with the nucleation of topological defects. The pressure gradients and the velocity characterize how boundary effects drive system-wide dynamics. And the forces link the underlying fluid with the nematic tensor to reveal the time scales of the system. More broadly, our work establishes a generalizable approach to quantitatively study experimental systems that are inaccessible to measuring probes.

cond-mat.soft↗

arXiv2022

Convex Quantization Preserves Logconcavity

A logconcave likelihood is as important to proper statistical inference as a convex cost function is important to variational optimization. Quantization is often disregarded when writing likelihood models, ignoring the limitations of the physical detectors used to collect the data. These two facts call for the question: would including quantization in likelihood models preclude logconcavity? are the true data likelihoods logconcave? We provide a general proof that the same simple assumption that leads to logconcave continuous-data likelihoods also leads to logconcave quantized-data likelihoods, provided that convex quantization regions are used.

eess.SP↗

arXiv2022

Artifacts in optical projection tomography due to refractive index mismatch: model and correction

Optical Projection Tomography (OPT) is a powerful tool for 3D imaging of mesoscopic samples, thus of great importance to image whole organs for the study of various disease models in life sciences. OPT is able to achieve resolution at a few tens of microns over a large sample volume of several cubic centimeters. However, the reconstructed OPT images often suffer from artifacts caused by different kinds of physical miscalibration. This work focuses on the refractive index (RI) mismatch between the rotating object and the surrounding medium. We derive a 3D cone beam forward model to approximate the effect of RI mismatch and implement a fast and efficient reconstruction method to correct the induced seagull-shaped artifacts on experimental images of fluorescent beads.

physics.optics↗