Publications de Adrien Raphaël Depeursinge

Comparing various AI approaches to traditional quantitative assessment of the myocardial perfusion in [82Rb] PET for MACE prediction

Julien René Pierre Fageot, Adrien Raphaël Depeursinge, Daniel Abler

Assessing the individual risk of Major Adverse Cardiac Events (MACE) is of major importance as cardiovascular diseases remain the leading cause of death worldwide. Quantitative Myocardial Perfusion Imaging (MPI) parameters such as stress Myocardial Blood F ...

Nature Portfolio2024

Why is the winner the best?

Gabriel Girard, Jian Wang, Ho Ling Li, Adrien Raphaël Depeursinge, Yong Yang, Fan Xia, Xiao Wang, Jing Li, Hui Wang

International benchmarking competitions have become fundamental for the comparative performance assessment of image analysis methods. However, little attention has been given to investigating what can be learnt from these competitions. Do they really gener ...

Ieee Computer Soc2023

Principled Design and Implementation of Steerable Detectors

Michaël Unser, Zsuzsanna Püspöki, Julien René Pierre Fageot, Adrien Raphaël Depeursinge

We provide a complete pipeline for the detection of patterns of interest in an image. In our approach, the patterns are assumed to be adequately modeled by a known template, and are located at unknown positions and orientations that we aim at retrieving. W ...

2021

PET-based prognostic survival model after radiotherapy for head and neck cancer

Adrien Raphaël Depeursinge, Xiaolu Sun, Xin Sun

PurposeThe aims of this multicentre retrospective study of locally advanced head and neck cancer (LAHNC) treated with definitive radiotherapy were to (1) identify positron emission tomography (PET)-F-18-fluorodeoxyglucose (F-18-FDG) parameters correlated w ...

SPRINGER2019

The use of texture-based radiomics CT analysis to predict outcomes in early-stage non-small cell lung cancer treated with stereotactic ablative radiotherapy

Adrien Raphaël Depeursinge, Pierre Starkov

Objective: Stereotactic ablative radiotherapy (SABR) is being increasingly used as a non-invasive treatment for early-stage non-small cell lung cancer (NSCLC). A non-invasive method to estimate treatment outcomes in these patients would be valuable, especi ...

BRITISH INST RADIOLOGY2019

Neural network training for cross-protocol radiomic feature standardization in computed tomography

Adrien Raphaël Depeursinge

Radiomics has shown promising results in several medical studies, yet it suffers from a limited discrimination and informative capability as well as a high variation and correlation with the tomographic scanner types, pixel spacing, acquisition protocol, a ...

SPIE-SOC PHOTO-OPTICAL INSTRUMENTATION ENGINEERS2019

Revealing Tumor Habitats from Texture Heterogeneity Analysis for Classification of Lung Cancer Malignancy and Aggressiveness

Adrien Raphaël Depeursinge

We propose an approach for characterizing structural heterogeneity of lung cancer nodules using Computed Tomography Texture Analysis (CTTA). Measures of heterogeneity were used to test the hypothesis that heterogeneity can be used as predictor of nodule ma ...

Nature Research2019

Texture-driven parametric snakes for semi-automatic image segmentation

Michaël Unser, Adrien Raphaël Depeursinge, Anaïs Laure Marie-Thérèse Badoual

We present a texture-driven parametric snake for semi-automatic segmentation of a single and closed structure in an image. We propose a new energy functional that combines intensity and texture information. The two types of image information are balanced u ...

ACADEMIC PRESS INC ELSEVIER SCIENCE2019

Rotation Invariance and Directional Sensitivity: Spherical Harmonics versus Radiomics Features

Michaël Unser, Julien René Pierre Fageot, John Paul Ward, Adrien Raphaël Depeursinge

We define and investigate the Local Rotation Invariance (LRI) and Directional Sensitivity (DS) of radiomics features. Most of the classical features cannot combine the two properties, which are antagonist in simple designs. We propose texture operators bas ...

SPRINGER INTERNATIONAL PUBLISHING AG2018

(F-18)-FDG PET/CT parameters to predict survival and recurrence in patients with locally advanced cervical cancer treated with chemoradiotherapy

Adrien Raphaël Depeursinge

2018