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2020 – today
- 2024
[j4]Minh H. Vu, Anders Garpebring, Tufve Nyholm, Tommy Löfstedt:
Compressing the Activation Maps in Deep Convolutional Neural Networks and Its Regularizing Effect. Trans. Mach. Learn. Res. 2024 (2024)- 2023
- [j3]Attila Simkó, Simone Ruiter, Tommy Löfstedt, Anders Garpebring, Tufve Nyholm, Mikael Bylund, Joakim Jonsson:
Improving MR image quality with a multi-task model, using convolutional losses. BMC Medical Imaging 23(1): 148 (2023) - [c7]Attila Simkó, Anders Garpebring, Joakim Jonsson, Tufve Nyholm, Tommy Löfstedt:
Reproducibility of the Methods in Medical Imaging with Deep Learning. MIDL 2023: 95-106 - 2022
- [j2]Minh H. Vu
, Gabriella Norman, Tufve Nyholm, Tommy Löfstedt:
A Data-Adaptive Loss Function for Incomplete Data and Incremental Learning in Semantic Image Segmentation. IEEE Trans. Medical Imaging 41(6): 1320-1330 (2022) - [c6]Attila Simkó, Tommy Löfstedt, Anders Garpebring, Tufve Nyholm, Joakim Jonsson:
MRI bias field correction with an implicitly trained CNN. MIDL 2022: 1125-1138 - [i9]Sandeep Kaushik, Mikael Bylund, Cristina Cozzini, Dattesh Shanbhag, Steven F. Petit, Jonathan J. Wyatt, Marion I. Menzel, Carolin M. Pirkl, Bhairav Mehta, Vikas Chauhan, Kesavadas Chandrasekharan, Joakim Jonsson, Tufve Nyholm, Florian Wiesinger, Bjoern H. Menze:
Region of Interest focused MRI to Synthetic CT Translation using Regression and Classification Multi-task Network. CoRR abs/2203.16288 (2022) - [i8]Attila Simkó, Anders Garpebring, Joakim Jonsson, Tufve Nyholm, Tommy Löfstedt:
Reproducibility of the Methods in Medical Imaging with Deep Learning. CoRR abs/2210.11146 (2022) - 2021
- [c5]Attila Tibor Simkó, Tommy Löfstedt, Anders Garpebring, Mikael Bylund, Tufve Nyholm, Joakim Jonsson:
Changing the Contrast of Magnetic Resonance Imaging Signals using Deep Learning. MIDL 2021: 713-727 - [i7]Minh H. Vu, Gabriella Norman, Tufve Nyholm, Tommy Löfstedt:
A Data-Adaptive Loss Function for Incomplete Data and Incremental Learning in Semantic Image Segmentation. CoRR abs/2104.11020 (2021) - [i6]Raghav Mehta, Angelos Filos, Ujjwal Baid, Chiharu Sako, Richard McKinley, Michael Rebsamen, Katrin Dätwyler, Raphael Meier, Piotr Radojewski, Gowtham Krishnan Murugesan, Sahil S. Nalawade, Chandan Ganesh, Benjamin C. Wagner, Fang F. Yu, Baowei Fei, Ananth J. Madhuranthakam, Joseph A. Maldjian, Laura Alexandra Daza, Catalina Gómez Caballero, Pablo Arbeláez, Chengliang Dai, Shuo Wang, Hadrien Raynaud, Yuanhan Mo, Elsa D. Angelini, Yike Guo, Wenjia Bai, Subhashis Banerjee, Linmin Pei, Murat Ak, Sarahi Rosas-González, Ilyess Zemmoura, Clovis Tauber, Minh H. Vu, Tufve Nyholm, Tommy Löfstedt, Laura Mora Ballestar, Verónica Vilaplana, Hugh McHugh, Gonzalo D. Maso Talou, Alan Wang, Jay B. Patel, Ken Chang, Katharina Hoebel, Mishka Gidwani, Nishanth Thumbavanam Arun, Sharut Gupta, Mehak Aggarwal, Praveer Singh, Elizabeth R. Gerstner, Jayashree Kalpathy-Cramer, Nicolas Boutry, Alexis Huard, Lasitha Vidyaratne, Md Monibor Rahman, Khan M. Iftekharuddin, Joseph Chazalon, Élodie Puybareau, Guillaume Tochon, Jun Ma, Mariano Cabezas, Xavier Lladó, Arnau Oliver, Liliana Valencia, Sergi Valverde, Mehdi Amian, Mohammadreza Soltaninejad, Andriy Myronenko, Ali Hatamizadeh, Xue Feng, Quan Dou, Nicholas J. Tustison, Craig H. Meyer, Nisarg A. Shah, Sanjay N. Talbar, Marc-André Weber, Abhishek Mahajan, András Jakab, Roland Wiest, Hassan M. Fathallah-Shaykh, Arash Nazeri, Mikhail Milchenko, Daniel S. Marcus, Aikaterini Kotrotsou, Rivka Colen, John B. Freymann, Justin S. Kirby, Christos Davatzikos, Bjoern H. Menze, Spyridon Bakas, Yarin Gal, Tal Arbel:
QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Metrics and Benchmarking Results. CoRR abs/2112.10074 (2021) - 2020
- [j1]Minh H. Vu, Tommy Löfstedt, Tufve Nyholm, Raphael Sznitman:
A Question-Centric Model for Visual Question Answering in Medical Imaging. IEEE Trans. Medical Imaging 39(9): 2856-2868 (2020) - [c4]Minh H. Vu, Tufve Nyholm, Tommy Löfstedt:
Multi-decoder Networks with Multi-denoising Inputs for Tumor Segmentation. BrainLes@MICCAI (1) 2020: 412-423 - [i5]Minh H. Vu, Tommy Löfstedt, Tufve Nyholm, Raphael Sznitman:
A Question-Centric Model for Visual Question Answering in Medical Imaging. CoRR abs/2003.08760 (2020) - [i4]Minh H. Vu, Tufve Nyholm, Tommy Löfstedt:
Multi-Decoder Networks with Multi-Denoising Inputs for Tumor Segmentation. CoRR abs/2012.03684 (2020)
2010 – 2019
- 2019
- [c3]Minh H. Vu, Tufve Nyholm, Tommy Löfstedt:
TuNet: End-to-End Hierarchical Brain Tumor Segmentation Using Cascaded Networks. BrainLes@MICCAI (1) 2019: 174-186 - [c2]Minh H. Vu, Raphael Sznitman, Tufve Nyholm, Tommy Löfstedt:
Ensemble of Streamlined Bilinear Visual Question Answering Models for the ImageCLEF 2019 Challenge in the Medical Domain. CLEF (Working Notes) 2019 - [i3]Minh H. Vu, Tufve Nyholm, Tommy Löfstedt:
TuNet: End-to-end Hierarchical Brain Tumor Segmentation using Cascaded Networks. CoRR abs/1910.05338 (2019) - [i2]Minh H. Vu, Guus Grimbergen, Attila Simkó, Tufve Nyholm, Tommy Löfstedt:
End-to-End Cascaded U-Nets with a Localization Network for Kidney Tumor Segmentation. CoRR abs/1910.07521 (2019) - [i1]Minh H. Vu, Guus Grimbergen, Tufve Nyholm, Tommy Löfstedt:
Evaluation of Multi-Slice Inputs to Convolutional Neural Networks for Medical Image Segmentation. CoRR abs/1912.09287 (2019)
2000 – 2009
- 2008
- [c1]Thomas Boettger, Tufve Nyholm, Magnus Karlsson, Chandrasekhar Nunna, Juan Carlos Celi:
Radiation therapy planning and simulation with magnetic resonance images. Medical Imaging: Image-Guided Procedures 2008: 69181C
Coauthor Index
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