Tufve Nyholm

According to our database, Tufve Nyholm authored at least 15 papers between 2008 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2024

Compressing the Activation Maps in Deep Convolutional Neural Networks and Its Regularizing Effect.

Minh H. Vu, Anders Garpebring, Tufve Nyholm, Tommy Löfstedt

Trans. Mach. Learn. Res., 2024

2023

Improving MR image quality with a multi-task model, using convolutional losses.

Attila Simkó, Simone Ruiter, Tommy Löfstedt, Anders Garpebring, Tufve Nyholm, Mikael Bylund, Joakim Jonsson

BMC Medical Imaging, December, 2023

Reproducibility of the Methods in Medical Imaging with Deep Learning.

Attila Simkó, Anders Garpebring, Joakim Jonsson, Tufve Nyholm, Tommy Löfstedt

Proceedings of the Medical Imaging with Deep Learning, 2023

2022

A Data-Adaptive Loss Function for Incomplete Data and Incremental Learning in Semantic Image Segmentation.

Minh H. Vu, Gabriella Norman, Tufve Nyholm, Tommy Löfstedt

IEEE Trans. Medical Imaging, 2022

Region of Interest focused MRI to Synthetic CT Translation using Regression and Classification Multi-task Network.

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

CoRR, 2022

MRI bias field correction with an implicitly trained CNN.

Attila Simkó, Tommy Löfstedt, Anders Garpebring, Tufve Nyholm, Joakim Jonsson

Proceedings of the International Conference on Medical Imaging with Deep Learning, 2022

2021

QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Metrics and Benchmarking Results.

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

CoRR, 2021

Changing the Contrast of Magnetic Resonance Imaging Signals using Deep Learning.

Attila Tibor Simkó, Tommy Löfstedt, Anders Garpebring, Mikael Bylund, Tufve Nyholm, Joakim Jonsson

Proceedings of the Medical Imaging with Deep Learning, 7-9 July 2021, Lübeck, Germany., 2021

2020

A Question-Centric Model for Visual Question Answering in Medical Imaging.

Minh H. Vu, Tommy Löfstedt, Tufve Nyholm, Raphael Sznitman

IEEE Trans. Medical Imaging, 2020

Multi-decoder Networks with Multi-denoising Inputs for Tumor Segmentation.

Minh H. Vu, Tufve Nyholm, Tommy Löfstedt

Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2020

2019

Evaluation of Multi-Slice Inputs to Convolutional Neural Networks for Medical Image Segmentation.

Minh H. Vu, Guus Grimbergen, Tufve Nyholm, Tommy Löfstedt

CoRR, 2019

End-to-End Cascaded U-Nets with a Localization Network for Kidney Tumor Segmentation.

Minh H. Vu, Guus Grimbergen, Attila Simkó, Tufve Nyholm, Tommy Löfstedt

CoRR, 2019

Ensemble of Streamlined Bilinear Visual Question Answering Models for the ImageCLEF 2019 Challenge in the Medical Domain.

Minh H. Vu, Raphael Sznitman, Tufve Nyholm, Tommy Löfstedt

Proceedings of the Working Notes of CLEF 2019, 2019

TuNet: End-to-End Hierarchical Brain Tumor Segmentation Using Cascaded Networks.

Minh H. Vu, Tufve Nyholm, Tommy Löfstedt

Proceedings of the Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries, 2019

2008

Radiation therapy planning and simulation with magnetic resonance images.

Thomas Boettger, Tufve Nyholm, Magnus Karlsson, Chandrasekhar Nunna, Juan Carlos Celi

Proceedings of the Medical Imaging 2008: Visualization, 2008