Jean-Philippe Thiran

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Recently, many pulse-echo ultrasound (US) imaging methods have relied on the transmission of unfocused wavefronts. Such a strategy allows for very high frame rates at the cost of a degraded image quality. In this work, we present a regularized inverse prob ...

In the last five years, Deep Brain Stimulation (DBS) has become the most popular and effective surgical technique for the treatment of Parkinson s disease (PD). The Subthalamic Nucleus (STN) is the usual target involved when applying DBS. Unfortunately, the STN is in general not visible in common medical imaging modalities. Therefore, atlas-based segmentation is commonly considered to locate it in the images. In this paper, we propose a scheme that allows both, to perform a comparison between different regi

In recent years, methods estimating the spatial distribution of tissue speed of sound with pulse-echo ultrasound are gaining considerable traction. They can address limitations of B-mode imaging, for instance in diagnosing fatty liver diseases. Current sta ...

Databases of normative values from healthy tissues are needed to leverage the improved comparability and hardware independence of quantitative MRI, and thus enable patient-specific detection of abnormalities in visual interpretation. Here, we present normative atlases of T1 relaxation times in the brain at 3T (1 mm isotropic) and 7T (0.6 mm isotropic) from two large cohorts of healthy subjects. The atlases were tested in single‐subject comparisons for detection of abnormal relaxation times in patients scann

Ultrasound imaging is a technique widely used in medicine to visualize organs and other body structures, capturing their position, size, morphology and any pathological lesions. Its use is unfortunately limited to specialized centers with trained personnel ...

The goal of out-of-distribution (OoD) detection is to identify unseen categories of inputs different from those seen during training, which is an important requirement for the safe deployment of deep neural networks in computational pathology. Additionally ...

Myelin water imaging is an MRI technique used to quantify myelination in the brain. The state-of-the-art reconstruction method is based on non-negative least squares optimization with zero-order Tikhonov regularization. In this study, a second-order Tikhonov regularization approach with control points was examined. This penalty term is more efficient for promoting smooth solutions while minimizing the contamination between myelin and non-myelin components. The performance of the proposed algorithm was inves

This paper presents an ITK implementation for exporting the contours of the automated segmentation results to DICOM-RT Structure Set format. The “radiotherapy structure set” (RTSTRUCT) object of the DICOM standard is used for the transfer of patient structures and related data, between the devices found within and outside the radiotherapy department. It mainly contains the information of regions of interest (ROIs) and points of interest (E.g. dose reference points). In many cases, rather than manually drawi

We present the comparison of two-dimensional (2D) fetal brain biometry on magnetic resonance (MR) images using orthogonal 2D T2-weighted sequences (T2WSs) vs. one 3D super-resolution (SR) reconstructed volume and evaluation of the level of confidence and c ...

Whole brain DSI acquisitions are now clinically feasible. It is therefore necessary to have scalar maps available in order to easily visualize summary statistics of the full 3D diffusion pdf available in every voxel. We show how to derive from DSI not only ...

An eye gaze tracking system is disclosed. The system includes a gaze data acquisition system including a plurality of light sources and a plurality of image sensors. The plurality of light sources are arranged to emit light to a head of the user, and the p ...

OBJECTIVE The authors developed a new, real-time interactive inverse planning approach, based on a fully convex framework, to be used for Gamma Knife radiosurgery. ...

Conventional magnetic resonance imaging (MRI) of patients with multiple sclerosis provides only limited insights into the nature of brain tissue damage with modest clinical-radiological correlations. In this study, quantitative and semi-quantitative MRI te ...

We present HOTmix, a new model to describe the diffusion MRI signal for molecules undergoing hindered diffusion. HOTmix is based on a mixture of generalized higher order tensors, explicitly incorporating the diffusion sequence’s time-dependent parameters. The method was evaluated on simulated diffusion MRI signals obtained through Monte Carlo simulations, using intermediate diffusion times, mimicking both ex-vivo and in-vivo conditions. HOTmix provided better reconstructions compared to the standard diffusi

We present a new dataset for form understanding in noisy scanned documents (FUNSD) that aims at extracting and structuring the textual content of forms. The dataset comprises 199 real, fully annotated, scanned forms. The documents are noisy and vary widely ...

We propose Independent Component Analysis representation and Support Vector Machine classification to extract facial features in a face detection/localization context. The goal is to find a better space where project the data in order to build ten different face-feature classifiers that are robust to illumination variations and bad environment conditions. The method was tested on the BANCA database, in different scenarios: controlled conditions, degraded conditions and adverse conditions.

Validation is the main bottleneck preventing the adoption of many medical image processing algorithms in the clinical practice. In the classical approach, a-posteriori analysis is performed based on some objective metrics. In this work, a different approac ...

The diagnosis of sleep disorders is still often based on polysomnography, an in-lab exam allowing experts to perform accurate sleep staging, although this is labor-intensive, expensive, and exposing patients to unusual sleep conditions. A state-of-the-art ...

After a major flood catastrophe, a precious information is the delineation of the affected areas. Remote sensing imagery, especially synthetic aperture radar, allows to obtain a global and complete view of the situation. However, the detection of the flood ...

This paper presents 3-D brain tissue classification schemes using three recent promising energy minimization methods for Markov random fields: graph cuts, loopy belief propagation and tree-reweighted message passing. The classification is performed using t ...

Jean-Philippe Thiran

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On Problem Formulation, Efficient Modeling and Deep Neural Networks for High-Quality Ultrasound Imaging

Cross Validation of Experts Versus Registration Methods for Target Localization in Deep Brain Stimulation

Windowed Radon Transform for Robust Speed-of-Sound Imaging With Pulse-Echo Ultrasound

Submillimeter T1 Atlas for Subject-Specific Abnormality Detection at 7T

Assessment of Image Quality vs. Computation Cost for Different Parameterizations of Ultrasound Imaging Pipelines

SOoD: Self-Supervised Out-of-Distribution Detection Under Domain Shift for Multi-Class Colorectal Cancer Tissue Types

Robust myelin water imaging from multi-echo T2 data using second-order Tikhonov regularization with control points

Exporting Contours to DICOM-RT Structure Set

Fetal Brain Biometric Measurements on 3D Super-Resolution Reconstructed T2-Weighted MRI: An Intra- and Inter-observer Agreement Study

Deriving scalar maps from Diffusion Spectrum MRI

EYE GAZE TRACKING SYSTEM AND METHOD

A real-time optimal inverse planning for Gamma Knife radiosurgery by convex optimization: description of the system and first dosimetry data

Multicontrats MRI Improved the Clinico-Radiological Correlation in Early Multiple Sclerosis Patients with Minor Deficits

HOTmix: characterizing hindered diffusion using a mixture of generalized higher order tensors

FUNSD: A Dataset for Form Understanding in Noisy Scanned Documents

Independent Component Analysis and Support Vector Machine for Face Feature Extraction

Towards a diffusion image processing validation and accuracy prediction framework

PPG-Based Sleep Staging Using SleepPPGNet: Extension to Wearables, Improvements, Limitations

Detection of Floods In Sar Images with Non-Linear Kernel Clustering and Topographic Prior

Comparison of Energy Minimization Methods for 3-D Brain Tissue Classification