Jean-Philippe Thiran

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In this paper, we tackle the problem of unsupervised classification of hyperspectral images. We propose a clustering method based on graphs representing the data structure, which is assumed to be an union of multiple manifolds. The method constraints the p ...

The main limitation of diffusion tractography for connectivity studies is that the reconstructed tractograms are not truly quantitative. Microstructure imaging allows the estimation of more quantitative features of the neuronal tissue, such as the axon diameter distribution, but this analysis can only be performed voxelwise. Here, we extend a framework that we recently proposed for evaluating the plausibility of tractograms (COMMIT) with the aim of assessing bundle-specific axon diameter distributions as we

Cytology is an option for triaging human papillomavirus (HPV)-positive women. The interpretation of cytologic slides requires expertise and financial resources that are not always available in resource-limited settings. A solution could be offered by manua ...

We discuss a novel sampling theorem on the sphere developed by McEwen & Wiaux recently through an association between the sphere and the torus. To represent a band-limited signal exactly, this new sampling theorem requires less than half the number of samp ...

This paper proposes to apply the non parametric atlas registration framework we have recently developed in [6]. This technique derived from the optical flow model and the active contour framework allows to base the registration of an anatomical atlas on se ...

Balanced steady-state free-precession (bSSFP) is prone to local field inhomogeneities, typically appearing as signal voids, i.e. banding-artifacts. A new method, termed true constructive interference in steady state (trueCISS), is proposed based on the acquisition of eight highly undersampled bSSFP k-spaces with different radio-frequency (RF) phase increments. A model-based non-linear inversion is used to fit the bSSFP signal model onto the undersampled data, effectively estimating parameter maps that allow

Classical ultrasound image reconstruction mainly relies on the well-known delay-and-sum (DAS) beamforming for its simplicity and real-time capability. Sparse regularization methods propose an alternative to DAS which lead to a better inversion of the ill-p ...

This paper proposes an image segmentation model based on the active contour model, the Mumford-Shah functional and the image decomposition process. Generally speaking, the active contour model detects boundaries in images from sharp intensities variations and the Mumford-Shah model finds smooth regions from homogeneous intensities. Our model merges these two complementary approaches while considering the Four Color Theorem to globally partition any given image. We also consider the textural part lying in na

In this paper we address the problem of multi-object tracking in video sequences, with application to pedestrian tracking in a crowd. In this con- text, particle ¯lters provide a robust tracking framework under ambiguity conditions. The particle ¯lter technique is used in this work, but in order to reduce its computational complexity and increase its robustness, we propose to track the moving objects by generating hypotheses not in the image plan but on the top-view reconstruction of the scene. Compara- tiv

Motivation: Constrained Spherical Deconvolution (CSD) is a state-of-the-art method for estimating the fiber orientation distribution function (fODF) in white matter from diffusion MRI data. However, CSD faces limitations in resolving fiber crossings with small inter-fiber angles when using low spherical harmonic order and produces noisy fODFs when using high order. Goal(s): This study aims to improve the stability and angular resolution of fODFs from CSD. Approach: We extend the CSD estimation framework by

We propose a new multiscale image segmentation model, based on the active contour/snake model and the Polyakov action. The concept of scale, general issue in physics and signal processing, is introduced in the active contour model, which is a well-known im ...

Purpose of review ...

This paper presents a new and original variational framework for atlas-based segmentation. The proposed framework integrates both the active contour framework, and the dense deformation fields of optical flow framework. This framework is quite general and ...

The human primary auditory cortex is surrounded by at least six other, anatomically distinct areas that process auditory information. We have investigated their specialization with respect to sound recognition or sound localization with triple epoch functi ...

This dataset contains a collection of ultrafast ultrasound acquisitions from nine volunteers and the CIRS 054G phantom. For a comprehensive understanding of the dataset, please refer to the paper: Viñals, R.; Thiran, J.-P. A KL Divergence-Based Loss for In ...

The active contour/snake model is one of the most successful variational models in image segmentation. It consists of evolving a contour in images toward the boundaries of objects. Its success is based on strong mathematical properties and efficient numeri ...

A sampling theorem on the sphere has been developed recently, requiring half as many samples as alternative equiangular sampling theorems on the sphere. A reduction by a factor of two in the number of samples required to represent a band-limited signal on ...

In this paper we consider the problem of automatic extraction of the geometric lip features for the purposes of multi-modal speaker identification. The use of visual information from the mouth region can be of great importance for improving the speaker identification system performance in noisy conditions. We propose a novel method for automated lip features extraction that utilizes color space transformation and a fuzzy-based c-means clustering technique. Using the obtained visual cues closed-set audio-vis

Diffusion spectrum imaging (DSI) is increasingly explored in clinical research. The quantitative value of the DSI technique, however, has still to be established. In this context, a better understanding of the reproducibility and the anatomical corresponde ...

Jean-Philippe Thiran

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Non-linear Low-rank and Sparse Representation for Hyperspectral Image Analysis

Assessment of bundle-specific axon diameter distributions using diffusion MRI tractography

Telecytologic diagnosis of cervical smears for triage of self-sampled human papillomavirus–positive women in a resource-limited setting: concept development before implementation

Sampling theorems and compressive sensing on the sphere

Hierarchical Image Registration with an Active Contour-Based Atlas Registration Model

TrueCISS: Genuine bSSFP Signal Reconstruction from Undersampled Multiple-Acquisition SSFP Using Model-Based Iterative Non-Linear Inversion

Morphological component analysis for sparse regularization in plane wave imaging

Image Segmentation Model Using Active contour and Image Decomposition

Multi-Object Tracking using the Particle Filter Algorithm on the Top-View Plan

Beekeeping - artificial neural networks to fight varroa

Spatially Regularized Super-Resolved Constrained Spherical Deconvolution (SR2-CSD) of diffusion MRI data

Multiscale Active Contours

A nation-wide initiative for brain imaging and clinical phenotype data federation in Swiss university memory centres

Active Deformation Fields: Dense Deformation Field Estimation for Atlas-based Segmentation using the Active Contour Framework

Human auditory belt areas specialized in sound recognition: a functional magnetic resonance imaging study

A KL Divergence-Based Loss for In Vivo Ultrafast Ultrasound Image Enhancement with Deep Learning: Dataset (6/6)

Fast Global Minimization of the Active Contour/Snake Model

Implications for compressed sensing of a new sampling theorem on the sphere

Automatic extraction of geometric lip features with application to multi-modal speaker identification

On the reproducibility and anatomical correspondence of DSI tractography