Publications associées à Segmentation of head and neck lymph node regions for radiotherapy planning, using active contour based atlas registration

Computation of sensitivity coefficients in fixed source simulations with SERPENT2

Within the scope of the implementation of a nuclear data pipeline aiming at producing the best possible evaluated nuclear data files, a major point is the production of relevant sensitivity coefficients when including integral benchmark information. Thanks ...

Elsevier Science Sa2024

BigNeuron: a resource to benchmark and predict performance of algorithms for automated tracing of neurons in light microscopy datasets

Pascal Fua, Sean Lewis Hill, Amos Sironi, Jiancheng Yang, Jian Zhou, Siqi Liu, Xiang Li, Jie Zhou

BigNeuron is an open community bench-testing platform with the goal of setting open standards for accurate and fast automatic neuron tracing. We gathered a diverse set of image volumes across several species that is representative of the data obtained in m ...

2023

Compressed sensing (CS) MP2RAGE versus standard MPRAGE: A of derived brain volume measurements

Tobias Kober, Tom Hilbert, Gian Franco Piredda

Purpose: T1 Magnetization Prepared Two Rapid Acquisition Gradient Echo (MP2RAGE) with compress sensing (CS) has been proposed as an improvement of the standard MPRAGE sequence with multiple advantages including reduced acquisition time needed to provide a ...

ELSEVIER SCI LTD2022

Weakly Supervised Volumetric Image Segmentation with Deformed Templates

Pascal Fua, Pamuditha Udaranga Wickramasinghe, Patrick Moller Jensen, Mian Akbar Shah

There are many approaches to weakly-supervised training of networks to segment 2D images. By contrast, existing approaches to segmenting volumetric images rely on full-supervision of a subset of 2D slices of the 3D volume. We propose an approach to volume ...

Springer2022

Evaluating salient object detection in natural images with multiple objects having multi-level saliency

Sabine Süsstrunk, Gökhan Yildirim

Salient object detection is evaluated using binary ground truth (GT) with the labels being salient object class and background. In this study, the authors corroborate based on three subjective experiments on a novel image dataset that objects in natural im ...

2020

Myeloid Cells Orchestrate Systemic Immunosuppression, Impairing the Efficacy of Immunotherapy against HPV+ Cancers

Melody Swartz, Nadine Fournier, Douglas Hanahan, Stephan Wullschleger, Gabriele Galliverti, Mélanie Louise Tichet

Cancers induced by human papillomaviruses (HPV) should be responsive to immunotherapy by virtue of expressing the immunogenic oncoproteins E6/E7. However, advanced forms of cervical cancer, driven by HPV, are poorly responsive to immune response-enhancing ...

AMER ASSOC CANCER RESEARCH2020

Model-Class Selection Using Clustering and Classification for Structural Identification and Prediction

Ian Smith, Sai Ganesh Sarvotham Pai, Masoud Sanayei

Structural identification using physics-based models and subsequent prediction have much potential to enhance civil infrastructure asset-management decision-making. Interpreting monitoring information in the presence of multiple uncertainty sources and sys ...

2021

Comparison of crack segmentation using digital image correlation measurements and deep learning

Radhakrishna Achanta, Katrin Beyer, Amir Rezaie, Michele Godio

Reliable methods for detecting pixels that represent cracks from laboratory images taken for digital image correlation (DIC) are required for two main reasons. Firstly, the segmented crack maps are used as an input for some DIC methods that are based on di ...

2020

Automated CT bone segmentation using statistical shape modelling and local template matching

Alexandre Terrier, Philippe Büchler, Alain Farron, Elham Taghizadeh

Accurate CT bone segmentation is essential to develop chair-side manufacturing of implants based on additive manufacturing. We herewith present an automated method able to accurately segment challenging bone regions, while simultaneously providing anatomic ...

2019

Geometry in active learning for binary and multi-class image segmentation

Pascal Fua, Raphael Sznitman, Ksenia Konyushkova

We propose an active learning approach to image segmentation that exploits geometric priors to speed up and streamline the annotation process. It can be applied for both background foreground and multi-class segmentation tasks in 2D images and 3D image vol ...

2019

Brain tissue segmentation based on MP2RAGE multi-contrast images in 7 T MRI

Tobias Kober

We proposed a method for segmentation of brain tissues-gray matter, white matter, and cerebrospinal fluid-using multi-contrast images, including a T1 map and a uniform T1-weighted image, from a magnetization-prepared 2 rapid acquisition gradient echoes (MP ...

2019

Enhanced MR Image Classification Using Hybrid Statistical and Wavelets Features

Mohammad Khaja Nazeeruddin

Classification of brain tumor is one of the most vital tasks within medical image processing. Classification of images greatly depends on the features extracted from the image, and thus, feature extraction plays a great role in the correct classification o ...

2019

Graph Spectral Analysis Of Voxel-Wise Brain Graphs From Diffusion-Weighted Mri

Dimitri Nestor Alice Van De Ville, Hamid Behjat, Anjali Bagunu Tarun

Non-invasive characterization of brain structure has been made possible by the introduction of magnetic resonance imaging (MRI). Graph modeling of structural connectivity has been useful, but is often limited to defining nodes as regions from a brain atlas ...

IEEE2019

Lymphatic vessel density is associated with CD8(+) T cell infiltration and immunosuppressive factors in human melanoma

Melody Swartz, Olivier Michielin, Natacha Anne-Sophie Bordry, Manuel Andreas Fankhauser, Esther Danenberg, Maria Anna Sofia Broggi, Timothy Murray

Increased density of tumor-associated lymphatic vessels correlates with poor patient survival in melanoma and other cancers, yet lymphatic drainage is essential for initiating an immune response. Here we asked whether and how lymphatic vessel density (LVD) ...

TAYLOR & FRANCIS INC2018

Personalized Anatomic Eye Model From T1-Weighted Volume Interpolated Gradient Echo Magnetic Resonance Imaging of Patients With Uveal Melanoma

Alessia Pica, Meritxell Bach Cuadra, Raphael Sznitman

Purpose: We present a 3-dimensional patient-specific eye model from magnetic resonance imaging (MRI) for proton therapy treatment planning of uveal melanoma (UM). During MRI acquisition of UM patients, the point fixation can be difficult and, together with ...

ELSEVIER SCIENCE INC2018

Development of a nano-adjuvant cancer vaccine and its evaluation for melanoma in combination with radiotherapy

Sylvie Hauert

Cancer is the second leading cause of death in the world and melanoma is the deadliest type of skin cancer. Although surgery, radiotherapy and chemotherapy are still standard treatments, the discovery of the role played by the immune system in cancer has a ...

EPFL2018

Advancing immunotherapy for HPV-related cancers: Improving therapeutic vaccination approaches and understanding the immunosuppressive role of myeloid cells

Gabriele Galliverti

Human Papilloma Viruses (HPVs) are the most common sexually transmitted agents worldwide, and chronic infection with oncogenic HPVs can lead to the development of lesions in the cervix, the vulva, and the head and neck region. In some patients, these lesio ...

EPFL2018

Template-based Monocular 3-D Shape Reconstruction And Tracking Using Laplacian Meshes

Tien Dat Ngo

This thesis addresses the problem of recovering the 3-D shape of a deformable object in single images, or image sequences acquired by a monocular video camera, given that a 3-D template shape and a template image of the object are available. While being a ...

EPFL2016

Fast and Robust Segmentation of the Striatum Using Deep Convolutional Neural Networks

Kyong Hwan Jin

Background: Automated segmentation of brain structures is an important task in structural and functional image analysis. We developed a fast and accurate method for the striatum segmentation using deep convolutional neural networks (CNN). New method: T1 ma ...

Elsevier2016

Template-free 3D Reconstruction of Poorly-textured Nonrigid Surfaces

Mathieu Salzmann, Fei Wang, Xinchao Wang

Two main classes of approaches have been studied to perform monocular nonrigid 3D reconstruction: Template-based methods and Non-rigid Structure from Motion techniques. While the first ones have been applied to reconstruct poorly-textured surfaces, they as ...

Springer Int Publishing Ag2016