Machine and deep learning methods for radiomics von Avanzo, Michele, Wei, Lise, Stancanello, Joseph, Vallières, Martin, Rao, Arvind, Morin, Olivier, Mattonen, Sarah A., El Naqa, Issam

Volltext

Deep learning in head & neck cancer outcome prediction von Diamant, André, Chatterjee, Avishek, Vallières, Martin, Shenouda, George, Seuntjens, Jan

Volltext

MRI features predict survival and molecular markers in diffuse lower-grade gliomas von Zhou, Hao, Vallières, Martin, Bai, Harrison X, Su, Chang, Tang, Haiyun, Oldridge, Derek, Zhang, Zishu, Xiao, Bo, Liao, Weihua, Tao, Yongguang, Zhou, Jianhua, Zhang, Paul, Yang, Li

Volltext

Responsible Radiomics Research for Faster Clinical Translation von Vallières, Martin, Zwanenburg, Alex, Badic, Bodgan, Cheze Le Rest, Catherine, Visvikis, Dimitris, Hatt, Mathieu

Volltext

Deep Learning to Distinguish Benign from Malignant Renal Lesions Based on Routine MR Imaging von Xi, Ianto Lin, Zhao, Yijun, Wang, Robin, Chang, Marcello, Purkayastha, Subhanik, Chang, Ken, Huang, Raymond Y., Silva, Alvin C., Vallieres, Martin, Habibollahi, Peiman, Fan, Yong, Zou, Beiji, Gade, Terence P., Zhang, Paul J., Soulen, Michael C., Zhang, Zishu, Bai, Harrison X., Stavropoulos, S. William

Volltext

The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping von Zwanenburg, Alex, Vallieres, Martin, Abdalah, Mahmoud A., Aerts, Hugo J. W. L., Andrearczyk, Vincent, Apte, Aditya, Ashrafinia, Saeed, Bakas, Spyridon, Beukinga, Roeloff, Boellaard, Ronald, Bogowicz, Marta, Boldrini, Luca, Buvat, Irene, Cook, Gary J. R., Davatzikos, Christos, Depeursinge, Adrien, Desseroit, Marie-Charlotte, Dinapoli, Nicola, Cuong Viet Dinh, Echegaray, Sebastian, El Naqa, Issam, Fedorov, Andriy Y., Gatta, Roberto, Gillies, Robert J., Goh, Vicky, Goetz, Michael, Guckenberger, Matthias, Ha, Sung Min, Hatt, Mathieu, Isensee, Fabian, Lambin, Philippe, Leger, Stefan, Leijenaar, Ralph T. H., Lenkowicz, Jacopo, Lippert, Fiona, Losnegard, Are, Maier-Hein, Klaus H., Morin, Olivier, Mueller, Henning, Napel, Sandy, Nioche, Christophe, Orlhac, Fanny, Pati, Sarthak, Pfaehler, Elisabeth A. G., Rahmim, Arman, Rao, Arvind U. K., Scherer, Jonas, Siddique, Muhammad Musib, Sijtsema, Nanna M., Fernandez, Jairo Socarras, Spezi, Emiliano, Steenbakkers, Roel J. H. M., Tanadini-Lang, Stephanie, Thorwarth, Daniela, Troost, Esther G. C., Upadhaya, Taman, Valentini, Vincenzo, van Dijk, Lisanne V., van Griethuysen, Joost, van Velden, Floris H. P., Whybra, Philip, Richter, Christian, Loeck, Steffen

Volltext

Radiomics strategies for risk assessment of tumour failure in head-and-neck cancer von Vallières, Martin, Kay-Rivest, Emily, Perrin, Léo Jean, Liem, Xavier, Furstoss, Christophe, Aerts, Hugo J. W. L., Khaouam, Nader, Nguyen-Tan, Phuc Felix, Wang, Chang-Shu, Sultanem, Khalil, Seuntjens, Jan, El Naqa, Issam

Volltext

Head and neck tumor segmentation in PET/CT: The HECKTOR challenge von 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

Volltext

External validation of a combined PET and MRI radiomics model for prediction of recurrence in cervical cancer patients treated with chemoradiotherapy von Lucia, François, Visvikis, Dimitris, Vallières, Martin, Desseroit, Marie-Charlotte, Miranda, Omar, Robin, Philippe, Bonaffini, Pietro Andrea, Alfieri, Joanne, Masson, Ingrid, Mervoyer, Augustin, Reinhold, Caroline, Pradier, Olivier, Hatt, Mathieu, Schick, Ulrike

Volltext

Development and Validation of Multiparametric MRI–based Radiomics Models for Preoperative Risk Stratification of Endometrial Cancer von Lefebvre, Thierry L., Ueno, Yoshiko, Dohan, Anthony, Chatterjee, Avishek, Vallières, Martin, Winter-Reinhold, Eric, Saif, Sameh, Levesque, Ives R., Zeng, Xing Ziggy, Forghani, Reza, Seuntjens, Jan, Soyer, Philippe, Savadjiev, Peter, Reinhold, Caroline

Volltext

Machine learning reveals multimodal MRI patterns predictive of isocitrate dehydrogenase and 1p/19q status in diffuse low- and high-grade gliomas von Zhou, Hao, Chang, Ken, Bai, Harrison X., Xiao, Bo, Su, Chang, Bi, Wenya Linda, Zhang, Paul J., Senders, Joeky T., Vallières, Martin, Kavouridis, Vasileios K., Boaro, Alessandro, Arnaout, Omar, Yang, Li, Huang, Raymond Y.

Volltext

Enhancement of multimodality texture-based prediction models via optimization of PET and MR image acquisition protocols: a proof of concept von Vallières, Martin, Laberge, Sébastien, Diamant, André, El Naqa, Issam

Volltext

A Deep Look Into the Future of Quantitative Imaging in Oncology: A Statement of Working Principles and Proposal for Change von Morin, Olivier, Vallières, Martin, Jochems, Arthur, Woodruff, Henry C., Valdes, Gilmer, Braunstein, Steve E., Wildberger, Joachim E., Villanueva-Meyer, Javier E., Kearney, Vasant, Yom, Sue S., Solberg, Timothy D., Lambin, Philippe

Volltext

MRI-Derived Radiomics to Guide Post-operative Management for High-Risk Prostate Cancer von Bourbonne, Vincent, Vallières, Martin, Lucia, François, Doucet, Laurent, Visvikis, Dimitris, Tissot, Valentin, Pradier, Olivier, Hatt, Mathieu, Schick, Ulrike

Volltext

Multi-task Bayesian model combining FDG-PET/CT imaging and clinical data for interpretable high-grade prostate cancer prognosis von Larose, Maxence, Archambault, Louis, Touma, Nawar, Brodeur, Raphaël, Desroches, Félix, Raymond, Nicolas, Bédard-Tremblay, Daphnée, LeBlanc, Danahé, Rasekh, Fatemeh, Hovington, Hélène, Neveu, Bertrand, Vallières, Martin, Pouliot, Frédéric

Volltext

External Validation of an MRI-Derived Radiomics Model to Predict Biochemical Recurrence after Surgery for High-Risk Prostate Cancer von Bourbonne, Vincent, Fournier, Georges, Vallieres, Martin, Lucia, Francois, Doucet, Laurent, Tissot, Valentin, Cuvelier, Gilles, Hue, Stephane, Du, Henri Le Penn, Perdriel, Luc, Bertrand, Nicolas, Staroz, Frederic, Visvikis, Dimitris, Pradier, Olivier, Hatt, Mathieu, Schick, Ulrike

Volltext

Electric Power Fuse Identification with Deep Learning von Giard-Leroux, Simon, Cleroux, Guillaume, Kulkarni, Shreyas Sunil, Bouffard, Francois, Vallieres, Martin

Volltext

Automatic Head and Neck Tumor segmentation and outcome prediction relying on FDG-PET/CT images: Findings from the second edition of the HECKTOR challenge von 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

Volltext

Patient-specific microdosimetry: a proof of concept von DeCunha, Joseph M, Villegas, Fernanda, Vallières, Martin, Torres, Jose, Camilleri-Broët, Sophie, Enger, Shirin A

Volltext

Deep Learning Based on MRI for Differentiation of Low‐ and High‐Grade in Low‐Stage Renal Cell Carcinoma von Zhao, Yijun, Chang, Marcello, Wang, Robin, Xi, Ianto Lin, Chang, Ken, Huang, Raymond Y, Vallières, Martin, Habibollahi, Peiman, Dagli, Mandeep S., Palmer, Matthew, Zhang, Paul J., Silva, Alvin C., Yang, Li, Soulen, Michael C., Zhang, Zishu, Bai, Harrison X., Stavropoulos, S. William

Volltext