Search Results - "Andrearczyk, Vincent"

Using filter banks in Convolutional Neural Networks for texture classification by Andrearczyk, Vincent, Whelan, Paul F.

“…•We adapt the CNN architecture to texture analysis.•We introduce an energy layer to discard the overall shape information and focus on texture features.•We…”
Get full text

Staining Invariant Features for Improving Generalization of Deep Convolutional Neural Networks in Computational Pathology by Otálora, Sebastian, Atzori, Manfredo, Andrearczyk, Vincent, Khan, Amjad, Müller, Henning

“…One of the main obstacles for the implementation of deep convolutional neural networks (DCNNs) in the clinical pathology workflow is their low capability to…”
Get full text

Making Radiomics More Reproducible across Scanner and Imaging Protocol Variations: A Review of Harmonization Methods by Mali, Shruti Atul, Ibrahim, Abdalla, Woodruff, Henry C, Andrearczyk, Vincent, Müller, Henning, Primakov, Sergey, Salahuddin, Zohaib, Chatterjee, Avishek, Lambin, Philippe

“…Radiomics converts medical images into mineable data via a high-throughput extraction of quantitative features used for clinical decision support. However,…”
Get full text

Comparing various AI approaches to traditional quantitative assessment of the myocardial perfusion in [82Rb] PET for MACE prediction by Bors, Sacha, Abler, Daniel, Dietz, Matthieu, Andrearczyk, Vincent, Fageot, Julien, Nicod-Lalonde, Marie, Schaefer, Niklaus, DeKemp, Robert, Kamani, Christel H., Prior, John O., Depeursinge, Adrien

“…Assessing the individual risk of Major Adverse Cardiac Events (MACE) is of major importance as cardiovascular diseases remain the leading cause of death…”
Get full text

Wide kernels and their DCT compression in convolutional networks for nuclei segmentation by Andrearczyk, Vincent, Oreiller, Valentin, Depeursinge, Adrien

“…The locality and spatial field of view of image operators have played a major role in image analysis, from hand-crafted to deep learning methods. In…”
Get full text

On the Scale Invariance in State of the Art CNNs Trained on ImageNet by Graziani, Mara, Lompech, Thomas, Müller, Henning, Depeursinge, Adrien, Andrearczyk, Vincent

“…The diffused practice of pre-training Convolutional Neural Networks (CNNs) on large natural image datasets such as ImageNet causes the automatic learning of…”
Get full text

Cleaning radiotherapy contours for radiomics studies, is it worth it? A head and neck cancer study by Fontaine, Pierre, Andrearczyk, Vincent, Oreiller, Valentin, Abler, Daniel, Castelli, Joel, Acosta, Oscar, De Crevoisier, Renaud, Vallières, Martin, Jreige, Mario, Prior, John O., Depeursinge, Adrien

“…•PET images features are more stable across different delineation of the same target.•Shape family features are more stable.•The survival model based on…”
Get full text

Convolutional neural network on three orthogonal planes for dynamic texture classification by Andrearczyk, Vincent, Whelan, Paul F.

“…•A new CNN framework is introduced to analyze DTs on three orthogonal planes.•Multiple texture specific CNNs are developed.•An analysis of the contribution of…”
Get full text

Local rotation invariance in 3D CNNs by Andrearczyk, Vincent, Fageot, Julien, Oreiller, Valentin, Montet, Xavier, Depeursinge, Adrien

“…•We introduce the idea of local rotation invariance in 3D convolutional networks.•We propose three implementations including the use of spherical harmonics and…”
Get full text

Automated Tumor Segmentation in Radiotherapy by Savjani, Ricky R., Lauria, Michael, Bose, Supratik, Deng, Jie, Yuan, Ye, Andrearczyk, Vincent

“…Autosegmentation of gross tumor volumes holds promise to decrease clinical demand and to provide consistency across clinicians and institutions for radiation…”
Get full text

Head and neck tumor segmentation in PET/CT: The HECKTOR challenge by Oreiller, Valentin, Andrearczyk, Vincent, Jreige, Mario, Boughdad, Sarah, Elhalawani, Hesham, Castelli, Joel, Vallières, Martin, Zhu, Simeng, Xie, Juanying, Peng, Ying, Iantsen, Andrei, Hatt, Mathieu, Yuan, Yading, Ma, Jun, Yang, Xiaoping, Rao, Chinmay, Pai, Suraj, Ghimire, Kanchan, Feng, Xue, Naser, Mohamed A., Fuller, Clifton D., Yousefirizi, Fereshteh, Rahmim, Arman, Chen, Huai, Wang, Lisheng, Prior, John O., Depeursinge, Adrien

“…•The paper describes the first challenge on head and neck tumor segmentation in PET/CT.•Training (n=201, 4 centers) and test sets (n=53, 1 unseen center)…”
Get full text

Automatic Head and Neck Tumor segmentation and outcome prediction relying on FDG-PET/CT images: Findings from the second edition of the HECKTOR challenge by Andrearczyk, Vincent, Oreiller, Valentin, Boughdad, Sarah, Le Rest, Catherine Cheze, Tankyevych, Olena, Elhalawani, Hesham, Jreige, Mario, Prior, John O., Vallières, Martin, Visvikis, Dimitris, Hatt, Mathieu, Depeursinge, Adrien

“…By focusing on metabolic and morphological tissue properties respectively, FluoroDeoxyGlucose (FDG)-Positron Emission Tomography (PET) and Computed Tomography…”
Get full text

A global taxonomy of interpretable AI: unifying the terminology for the technical and social sciences by Graziani, Mara, Dutkiewicz, Lidia, Calvaresi, Davide, Amorim, José Pereira, Yordanova, Katerina, Vered, Mor, Nair, Rahul, Abreu, Pedro Henriques, Blanke, Tobias, Pulignano, Valeria, Prior, John O., Lauwaert, Lode, Reijers, Wessel, Depeursinge, Adrien, Andrearczyk, Vincent, Müller, Henning

“…Since its emergence in the 1960s, Artificial Intelligence (AI) has grown to conquer many technology products and their fields of application. Machine learning,…”
Get full text

Neural network training for cross-protocol radiomic feature standardization in computed tomography by Andrearczyk, Vincent, Depeursinge, Adrien, Müller, Henning

“…Radiomics has shown promising results in several medical studies, yet it suffers from a limited discrimination and informative capability as well as a high…”
Get full text

The Image Biomarker Standardization Initiative: Standardized Convolutional Filters for Reproducible Radiomics and Enhanced Clinical Insights by Whybra, Philip, Zwanenburg, Alex, Andrearczyk, Vincent, Schaer, Roger, Apte, Aditya P, Ayotte, Alexandre, Baheti, Bhakti, Bakas, Spyridon, Bettinelli, Andrea, Boellaard, Ronald, Boldrini, Luca, Buvat, Irène, Cook, Gary J R, Dietsche, Florian, Dinapoli, Nicola, Gabryś, Hubert S, Goh, Vicky, Guckenberger, Matthias, Hatt, Mathieu, Hosseinzadeh, Mahdi, Iyer, Aditi, Lenkowicz, Jacopo, Loutfi, Mahdi A L, Löck, Steffen, Marturano, Francesca, Morin, Olivier, Nioche, Christophe, Orlhac, Fanny, Pati, Sarthak, Rahmim, Arman, Rezaeijo, Seyed Masoud, Rookyard, Christopher G, Salmanpour, Mohammad R, Schindele, Andreas, Shiri, Isaac, Spezi, Emiliano, Tanadini-Lang, Stephanie, Tixier, Florent, Upadhaya, Taman, Valentini, Vincenzo, van Griethuysen, Joost J M, Yousefirizi, Fereshteh, Zaidi, Habib, Müller, Henning, Vallières, Martin, Depeursinge, Adrien

“…Filters are commonly used to enhance specific structures and patterns in images, such as vessels or peritumoral regions, to enable clinical insights beyond the…”
Get more information

Disentangling Neuron Representations with Concept Vectors by O'Mahony, Laura, Andrearczyk, Vincent, Muller, Henning, Graziani, Mara

“…Mechanistic interpretability aims to understand how models store representations by breaking down neural networks into interpretable units. However, the…”
Get full text

Rotational 3D Texture Classification Using Group Equivariant CNNs by Andrearczyk, Vincent, Depeursinge, Adrien

“…Convolutional Neural Networks (CNNs) traditionally encode translation equivariance via the convolution operation. Generalization to other transformations has…”
Get full text

Disentangling Neuron Representations with Concept Vectors by O'Mahony, Laura, Andrearczyk, Vincent, Muller, Henning, Graziani, Mara

“…Mechanistic interpretability aims to understand how models store representations by breaking down neural networks into interpretable units. However, the…”
Get full text

EDUE: Expert Disagreement-Guided One-Pass Uncertainty Estimation for Medical Image Segmentation by Abutalip, Kudaibergen, Saeed, Numan, Sobirov, Ikboljon, Andrearczyk, Vincent, Depeursinge, Adrien, Yaqub, Mohammad

“…Deploying deep learning (DL) models in medical applications relies on predictive performance and other critical factors, such as conveying trustworthy…”
Get full text

Exploiting XAI maps to improve MS lesion segmentation and detection in MRI by Spagnolo, Federico, Molchanova, Nataliia, Pineda, Mario Ocampo, Melie-Garcia, Lester, Cuadra, Meritxell Bach, Granziera, Cristina, Andrearczyk, Vincent, Depeursinge, Adrien

“…To date, several methods have been developed to explain deep learning algorithms for classification tasks. Recently, an adaptation of two of such methods has…”
Get full text