no code implementations • 18 Sep 2023 • George Yiasemis, Nikita Moriakov, Jan-Jakob Sonke, Jonas Teuwen
In this study, we propose vSHARP (variable Splitting Half-quadratic ADMM algorithm for Reconstruction of inverse Problems), a novel DL-based method for solving ill-posed inverse problems arising in MI.
no code implementations • 28 Aug 2023 • Nikita Moriakov, Jim Peters, Ritse Mann, Nico Karssemeijer, Jos van Dijck, Mireille Broeders, Jonas Teuwen
Finally, for a subset of 100 mammograms with a malign mass and concurrent MRI examination available, we analyze the agreement between lesion volume on mammography and MRI, resulting in an intraclass correlation coefficient of 0. 81 [95% CI 0. 73 - 0. 87] for consistency and 0. 78 [95% CI 0. 66 - 0. 86] for absolute agreement.
no code implementations • 3 Jul 2023 • Tianyu Zhang, Luyi Han, Anna D'Angelo, Xin Wang, Yuan Gao, Chunyao Lu, Jonas Teuwen, Regina Beets-Tan, Tao Tan, Ritse Mann
DWIs with different b-values are fused to efficiently utilize the difference features of DWIs.
no code implementations • 9 Feb 2023 • Eric Marcus, Ray Sheombarsing, Jan-Jakob Sonke, Jonas Teuwen
Deep Neural Networks (DNNs) are widely used for their ability to effectively approximate large classes of functions.
no code implementations • 3 Feb 2023 • Tianyu Zhang, Tao Tan, Luyi Han, Xin Wang, Yuan Gao, Jonas Teuwen, Regina Beets-Tan, Ritse Mann
Then the multi-parameter fusion with attention module enables the interaction of the encoded information from different parameters through a set of algorithmic strategies, and applies different weights to the information through the attention mechanism after information fusion to obtain refined representation information.
1 code implementation • 1 Feb 2023 • Luyi Han, Tao Tan, Tianyu Zhang, Yunzhi Huang, Xin Wang, Yuan Gao, Jonas Teuwen, Ritse Mann
Multi-sequence MRIs can be necessary for reliable diagnosis in clinical practice due to the complimentary information within sequences.
no code implementations • 20 Jan 2023 • George Yiasemis, Clara I. Sánchez, Jan-Jakob Sonke, Jonas Teuwen
This work investigates the impact of the $k$-space subsampling scheme on the quality of reconstructed accelerated MRI measurements produced by trained DL models.
1 code implementation • 27 May 2022 • Teaghan O'Briain, Carlos Uribe, Kwang Moo Yi, Jonas Teuwen, Ioannis Sechopoulos, Magdalena Bazalova-Carter
To correct for respiratory motion in PET imaging, an interpretable and unsupervised deep learning technique, FlowNet-PET, was constructed.
1 code implementation • 22 Apr 2022 • Sarthak Pati, Ujjwal Baid, Brandon Edwards, Micah Sheller, Shih-han Wang, G Anthony Reina, Patrick Foley, Alexey Gruzdev, Deepthi Karkada, Christos Davatzikos, Chiharu Sako, Satyam Ghodasara, Michel Bilello, Suyash Mohan, Philipp Vollmuth, Gianluca Brugnara, Chandrakanth J Preetha, Felix Sahm, Klaus Maier-Hein, Maximilian Zenk, Martin Bendszus, Wolfgang Wick, Evan Calabrese, Jeffrey Rudie, Javier Villanueva-Meyer, Soonmee Cha, Madhura Ingalhalikar, Manali Jadhav, Umang Pandey, Jitender Saini, John Garrett, Matthew Larson, Robert Jeraj, Stuart Currie, Russell Frood, Kavi Fatania, Raymond Y Huang, Ken Chang, Carmen Balana, Jaume Capellades, Josep Puig, Johannes Trenkler, Josef Pichler, Georg Necker, Andreas Haunschmidt, Stephan Meckel, Gaurav Shukla, Spencer Liem, Gregory S Alexander, Joseph Lombardo, Joshua D Palmer, Adam E Flanders, Adam P Dicker, Haris I Sair, Craig K Jones, Archana Venkataraman, Meirui Jiang, Tiffany Y So, Cheng Chen, Pheng Ann Heng, Qi Dou, Michal Kozubek, Filip Lux, Jan Michálek, Petr Matula, Miloš Keřkovský, Tereza Kopřivová, Marek Dostál, Václav Vybíhal, Michael A Vogelbaum, J Ross Mitchell, Joaquim Farinhas, Joseph A Maldjian, Chandan Ganesh Bangalore Yogananda, Marco C Pinho, Divya Reddy, James Holcomb, Benjamin C Wagner, Benjamin M Ellingson, Timothy F Cloughesy, Catalina Raymond, Talia Oughourlian, Akifumi Hagiwara, Chencai Wang, Minh-Son To, Sargam Bhardwaj, Chee Chong, Marc Agzarian, Alexandre Xavier Falcão, Samuel B Martins, Bernardo C A Teixeira, Flávia Sprenger, David Menotti, Diego R Lucio, Pamela Lamontagne, Daniel Marcus, Benedikt Wiestler, Florian Kofler, Ivan Ezhov, Marie Metz, Rajan Jain, Matthew Lee, Yvonne W Lui, Richard McKinley, Johannes Slotboom, Piotr Radojewski, Raphael Meier, Roland Wiest, Derrick Murcia, Eric Fu, Rourke Haas, John Thompson, David Ryan Ormond, Chaitra Badve, Andrew E Sloan, Vachan Vadmal, Kristin Waite, Rivka R Colen, Linmin Pei, Murat AK, Ashok Srinivasan, J Rajiv Bapuraj, Arvind Rao, Nicholas Wang, Ota Yoshiaki, Toshio Moritani, Sevcan Turk, Joonsang Lee, Snehal Prabhudesai, Fanny Morón, Jacob Mandel, Konstantinos Kamnitsas, Ben Glocker, Luke V M Dixon, Matthew Williams, Peter Zampakis, Vasileios Panagiotopoulos, Panagiotis Tsiganos, Sotiris Alexiou, Ilias Haliassos, Evangelia I Zacharaki, Konstantinos Moustakas, Christina Kalogeropoulou, Dimitrios M Kardamakis, Yoon Seong Choi, Seung-Koo Lee, Jong Hee Chang, Sung Soo Ahn, Bing Luo, Laila Poisson, Ning Wen, Pallavi Tiwari, Ruchika Verma, Rohan Bareja, Ipsa Yadav, Jonathan Chen, Neeraj Kumar, Marion Smits, Sebastian R van der Voort, Ahmed Alafandi, Fatih Incekara, Maarten MJ Wijnenga, Georgios Kapsas, Renske Gahrmann, Joost W Schouten, Hendrikus J Dubbink, Arnaud JPE Vincent, Martin J van den Bent, Pim J French, Stefan Klein, Yading Yuan, Sonam Sharma, Tzu-Chi Tseng, Saba Adabi, Simone P Niclou, Olivier Keunen, Ann-Christin Hau, Martin Vallières, David Fortin, Martin Lepage, Bennett Landman, Karthik Ramadass, Kaiwen Xu, Silky Chotai, Lola B Chambless, Akshitkumar Mistry, Reid C Thompson, Yuriy Gusev, Krithika Bhuvaneshwar, Anousheh Sayah, Camelia Bencheqroun, Anas Belouali, Subha Madhavan, Thomas C Booth, Alysha Chelliah, Marc Modat, Haris Shuaib, Carmen Dragos, Aly Abayazeed, Kenneth Kolodziej, Michael Hill, Ahmed Abbassy, Shady Gamal, Mahmoud Mekhaimar, Mohamed Qayati, Mauricio Reyes, Ji Eun Park, Jihye Yun, Ho Sung Kim, Abhishek Mahajan, Mark Muzi, Sean Benson, Regina G H Beets-Tan, Jonas Teuwen, Alejandro Herrera-Trujillo, Maria Trujillo, William Escobar, Ana Abello, Jose Bernal, Jhon Gómez, Joseph Choi, Stephen Baek, Yusung Kim, Heba Ismael, Bryan Allen, John M Buatti, Aikaterini Kotrotsou, Hongwei Li, Tobias Weiss, Michael Weller, Andrea Bink, Bertrand Pouymayou, Hassan F Shaykh, Joel Saltz, Prateek Prasanna, Sampurna Shrestha, Kartik M Mani, David Payne, Tahsin Kurc, Enrique Pelaez, Heydy Franco-Maldonado, Francis Loayza, Sebastian Quevedo, Pamela Guevara, Esteban Torche, Cristobal Mendoza, Franco Vera, Elvis Ríos, Eduardo López, Sergio A Velastin, Godwin Ogbole, Dotun Oyekunle, Olubunmi Odafe-Oyibotha, Babatunde Osobu, Mustapha Shu'aibu, Adeleye Dorcas, Mayowa Soneye, Farouk Dako, Amber L Simpson, Mohammad Hamghalam, Jacob J Peoples, Ricky Hu, Anh Tran, Danielle Cutler, Fabio Y Moraes, Michael A Boss, James Gimpel, Deepak Kattil Veettil, Kendall Schmidt, Brian Bialecki, Sailaja Marella, Cynthia Price, Lisa Cimino, Charles Apgar, Prashant Shah, Bjoern Menze, Jill S Barnholtz-Sloan, Jason Martin, Spyridon Bakas
Although machine learning (ML) has shown promise in numerous domains, there are concerns about generalizability to out-of-sample data.
3 code implementations • CVPR 2022 • George Yiasemis, Jan-Jakob Sonke, Clarisa Sánchez, Jonas Teuwen
Magnetic Resonance Imaging can produce detailed images of the anatomy and physiology of the human body that can assist doctors in diagnosing and treating pathologies such as tumours.
no code implementations • 28 Oct 2021 • Ray Sheombarsing, Nikita Moriakov, Jan-Jakob Sonke, Jonas Teuwen
The effectiveness of the proposed method is demonstrated by delineating boundaries of simply connected domains (organs) in medical images using Debauches wavelets and comparing performance with a U-Net baseline.
no code implementations • 29 Sep 2021 • Ray Sheombarsing, Nikita Moriakov, Jan-Jakob Sonke, Jonas Teuwen
The effectiveness of the proposed method is demonstrated by delineating boundaries of simply connected domains (organs) in medical images using Debauches wavelets and comparing performance with a U-Net baseline.
no code implementations • 13 Sep 2021 • Yoni Schirris, Mendel Engelaer, Andreas Panteli, Hugo Mark Horlings, Efstratios Gavves, Jonas Teuwen
We present WeakSTIL, an interpretable two-stage weak label deep learning pipeline for scoring the percentage of stromal tumor infiltrating lymphocytes (sTIL%) in H&E-stained whole-slide images (WSIs) of breast cancer tissue.
1 code implementation • 17 Aug 2021 • George Yiasemis, Chaoping Zhang, Clara I. Sánchez, Jan-Jakob Sonke, Jonas Teuwen
In spite of its extensive adaptation in almost every medical diagnostic and examinatorial application, Magnetic Resonance Imaging (MRI) is still a slow imaging modality which limits its use for dynamic imaging.
1 code implementation • 20 Jul 2021 • Yoni Schirris, Efstratios Gavves, Iris Nederlof, Hugo Mark Horlings, Jonas Teuwen
For MSI prediction in a tumor-annotated and color normalized subset of TCGA-CRC (n=360 patients), contrastive self-supervised learning improves the tile supervision baseline from 0. 77 to 0. 87 AUROC, on par with our proposed DeepSMILE method.
no code implementations • ICCV 2021 • Andreas Panteli, Jonas Teuwen, Hugo Horlings, Efstratios Gavves
However, outside the setting of regular images, we are often confronted with a different situation.
no code implementations • 7 Feb 2021 • Fazael Ayatollahi, Shahriar B. Shokouhi, Ritse M. Mann, Jonas Teuwen
Purpose: We propose a deep learning-based computer-aided detection (CADe) method to detect breast lesions in ultrafast DCE-MRI sequences.
3 code implementations • 9 Dec 2020 • Matthew J. Muckley, Bruno Riemenschneider, Alireza Radmanesh, Sunwoo Kim, Geunu Jeong, Jingyu Ko, Yohan Jun, Hyungseob Shin, Dosik Hwang, Mahmoud Mostapha, Simon Arberet, Dominik Nickel, Zaccharie Ramzi, Philippe Ciuciu, Jean-Luc Starck, Jonas Teuwen, Dimitrios Karkalousos, Chaoping Zhang, Anuroop Sriram, Zhengnan Huang, Nafissa Yakubova, Yvonne Lui, Florian Knoll
Accelerating MRI scans is one of the principal outstanding problems in the MRI research community.
1 code implementation • 10 Nov 2020 • Youssef Beauferris, Jonas Teuwen, Dimitrios Karkalousos, Nikita Moriakov, Mattha Caan, George Yiasemis, Lívia Rodrigues, Alexandre Lopes, Hélio Pedrini, Letícia Rittner, Maik Dannecker, Viktor Studenyak, Fabian Gröger, Devendra Vyas, Shahrooz Faghih-Roohi, Amrit Kumar Jethi, Jaya Chandra Raju, Mohanasankar Sivaprakasam, Mike Lasby, Nikita Nogovitsyn, Wallace Loos, Richard Frayne, Roberto Souza
Deep-learning-based brain magnetic resonance imaging (MRI) reconstruction methods have the potential to accelerate the MRI acquisition process.
no code implementations • 11 Jun 2020 • Jonas Teuwen, Nikita Moriakov, Christian Fedon, Marco Caballo, Ingrid Reiser, Pedrag Bakic, Eloy García, Oliver Diaz, Koen Michielsen, Ioannis Sechopoulos
This study proposes a reconstruction algorithm for DBT based on deep learning specifically optimized for these tasks.
no code implementations • ICLR 2020 • Nikita Moriakov, Jonas Adler, Jonas Teuwen
It is known that the CycleGAN problem might admit multiple solutions, and our goal in this paper is to analyze the space of exact solutions and to give perturbation bounds for approximate solutions.
no code implementations • 24 Jan 2020 • Nikita Moriakov, Jonas Adler, Jonas Teuwen
It is known that the CycleGAN problem might admit multiple solutions, and our goal in this paper is to analyze the space of exact solutions and to give perturbation bounds for approximate solutions.
1 code implementation • 20 Oct 2019 • Patrick Putzky, Dimitrios Karkalousos, Jonas Teuwen, Nikita Miriakov, Bart Bakker, Matthan Caan, Max Welling
We, team AImsterdam, summarize our submission to the fastMRI challenge (Zbontar et al., 2018).
no code implementations • 17 Aug 2018 • Yeman Brhane Hagos, Albert Gubern Merida, Jonas Teuwen
At candidate level, AUC value of 0. 933 with 95% confidence interval of [0. 920, 0. 954] was obtained when symmetry information is incorporated in comparison with baseline architecture which yielded AUC value of 0. 929 with [0. 919, 0. 947] confidence interval.
no code implementations • 14 Aug 2018 • Nikita Moriakov, Koen Michielsen, Jonas Adler, Ritse Mann, Ioannis Sechopoulos, Jonas Teuwen
In this study we propose an extension of the Learned Primal-Dual algorithm for digital breast tomosynthesis.
no code implementations • 14 Aug 2018 • Joris van Vugt, Elena Marchiori, Ritse Mann, Albert Gubern-Mérida, Nikita Moriakov, Jonas Teuwen
We analyze two transfer learning settings: 1) unsupervised transfer, where Hologic data with soft lesion annotation at pixel level and Siemens unlabelled data are used to annotate images in the latter data; 2) weak supervised transfer, where exam level labels for images from the Siemens mammograph are available.
no code implementations • 19 Feb 2018 • Timothy de Moor, Alejandro Rodriguez-Ruiz, Albert Gubern Mérida, Ritse Mann, Jonas Teuwen
In conclusion, the method could be used as a candidate selection model with high accuracy and with the additional information of lesion segmentation.
no code implementations • 15 Jan 2018 • Mohsen Ghafoorian, Jonas Teuwen, Rashindra Manniesing, Frank-Erik de Leeuw, Bram van Ginneken, Nico Karssemeijer, Bram Platel
To show this, we use noisy segmentation labels generated by a conventional region growing algorithm to train a deep network for lateral ventricle segmentation.