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Adrien Raphaël Depeursinge

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Related publications (21)

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

Adrien Raphaël Depeursinge, Xiaolu 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

Optimized Distributed Hyperparameter Search and Simulation for Lung Texture Classification in CT Using Hadoop

Adrien Raphaël Depeursinge

Many medical image analysis tasks require complex learning strategies to reach a quality of image-based decision support that is sufficient in clinical practice. The analysis of medical texture in tomographic images, for example of lung tissue, is no excep ...

2016

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

Automated Classification of Brain Tumor Type in Whole-Slide Digital Pathology Images Using Local Representative Tiles

Adrien Raphaël Depeursinge

Computerized analysis of digital pathology images offers the potential of improving clinical care (e.g. automated diagnosis) and catalyzing research (e.g. discovering disease subtypes). There are two key challenges thwarting computerized analysis of digita ...

Elsevier2016

Holographic Visualisation and Interaction of Fused CT, PET and MRI Volumetric Medical Imaging Data Using Dedicated Remote GPGPU Ray Casting

Patric Hagmann, Stéphane Gobron, Adrien Raphaël Depeursinge

Medical experts commonly use imaging including Computed Tomography (CT), Positron-Emission Tomography (PET) and Magnetic Resonance Imaging (MRI) for diagnosis or to plan a surgery. These scans give a highly detailed representation of the patient anatomy, b ...

SPRINGER INTERNATIONAL PUBLISHING AG2018

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

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

Julien René Fageot, Adrien Raphaël Depeursinge

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

Combining Unsupervised Feature Learning and Riesz Wavelets for Histopathology Image Representation: Application to Identifying Anaplastic Medulloblastoma

Adrien Raphaël Depeursinge

Medulloblastoma (MB) is a type of brain cancer that represent roughly 25% of all brain tumors in children. In the anaplastic medulloblastoma subtype, it is important to identify the degree of irregularity and lack of organizations of cells as this correlat ...

Springer Int Publishing Ag2015

A 3-D Riesz-Covariance Texture Model for Prediction of Nodule Recurrence in Lung CT

Adrien Raphaël Depeursinge

This paper proposes a novel imaging biomarker of lung cancer relapse from 3-D texture analysis of CT images. Three-dimensional morphological nodular tissue properties are described in terms of 3-D Riesz-wavelets. The responses of the latter are aggregated ...

Institute of Electrical and Electronics Engineers2016

Why is the winner the best?

Jian Wang, Ho Ling Li, Gabriel Girard, Adrien Raphaël Depeursinge

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

Metabolic Tumor Volume and Total Lesion Glycolysis in Oropharyngeal Cancer Treated With Definitive Radiotherapy: Which Threshold Is the Best Predictor of Local Control?

Adrien Raphaël Depeursinge

Purpose In the context of oropharyngeal cancer treated with definitive radiotherapy, the aim of this retrospective study was to identify the best threshold value to compute metabolic tumor volume (MTV) and/or total lesion glycolysis to predict local-region ...

Lippincott Williams & Wilkins2017

3D Solid Texture Classification Using Locally-Oriented Wavelet Transforms

Adrien Raphaël Depeursinge

Many image acquisition techniques used in biomedical imaging, material analysis, and structural geology are capable of acquiring 3D solid images. Computational analysis of these images is complex but necessary, since it is difficult for humans to visualize ...

IEEE2017

Optimized Steerable Wavelets for Texture Analysis of Lung Tissue In 3-D CT: Classification of Usual Interstitial Pneumonia

Michaël Unser, Adrien Raphaël Depeursinge, Pedram Pad

Our aim is to optimize wavelet-based feature extraction for differentiating between the classical versus atypical pattern of usual interstitial pneumonia (UIP) in volumetric CT. Our proposal is to act on the bandwidth of steerable wavelets while maintainin ...

IEEE2015

Multidimensional Texture Analysis for Improved Prediction of Ultrasound Liver Tumor Response to Chemotherapy Treatment

Dimitri Nestor Alice Van De Ville, Adrien Raphaël Depeursinge

The number density of scatterers in tumor tissue contribute to a heterogeneous ultrasound speckle pattern that can be difficult to discern by visual observation. Such tumor stochastic behavior becomes even more challenging if the tumor texture heterogeneit ...

Springer2016

A PET-Based Nomogram for Oropharyngeal Cancers

Adrien Raphaël Depeursinge

Purpose: In the context of locally advanced oropharyngeal cancer (LAOC) treated with definitive radiotherapy (RT) (combined with chemotherapy or cetuximab), the aims of this study were: (1) to identify PET-FDG parameters correlated with overall survival (O ...

10.1016/j.ejca.2017.01.0182017

Lung Tissue Classification Using Wavelet Frames

Michaël Unser, Daniel Sage, Adrien Raphaël Depeursinge

We describe a texture classification system that identifies lung tissue patterns from high-resolution computed tomography (HRCT) images of patients affected with interstitial lung diseases (ILD). This pattern recognition task is part of an image-based diag ...

IEEE2007

Principled Design and Implementation of Steerable Detectors

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

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

Rotation Invariance and Directional Sensitivity: Spherical Harmonics versus Radiomics Features

Michaël Unser, Julien René 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

Overview of the Predictive Value of Quantitative 18 FDG PET in Head and Neck Cancer Treated with Chemoradiotherapy

Adrien Raphaël Depeursinge

18 F-fluorodeoxyglucose (18F-FDG) positron emission tomography/computed tomography (PET/CT) allows to quantify the metabolic activity of a tumor (glycolysis) and has become a reference tool in oncology for the staging, restaging, radiotherapy planning and ...

Elsevier2016

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

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