Tufve Nyholm

23 papers B 1Journal 15Unranked 7
YearRankTypeTitle / Venue / Authors
2025 J jnl
From Promise to Practice: A Study of Common Pitfalls Behind the Generalization Gap in Machine Learning.
Trans. Mach. Learn. Res.
Saeideh Ghanbari Azar, Lorenzo Tronchin, Attila Simkó, Tufve Nyholm, Tommy Löfstedt
2025 B conf
Rethinking the DeepSMOTE Penalty Term and its Role in Imbalanced Learning.
ICTAI
Saeideh Ghanbari Azar, Tufve Nyholm, Tommy Löfstedt
2025 J jnl
Using Synthetic Images to Augment Small Medical Image Datasets.
CoRR
Minh H. Vu, Lorenzo Tronchin, Tufve Nyholm, Tommy Löfstedt
2024 J jnl
Compressing the Activation Maps in Deep Convolutional Neural Networks and Its Regularizing Effect.
Trans. Mach. Learn. Res.
Minh H. Vu, Anders Garpebring, Tufve Nyholm, Tommy Löfstedt
2023 J jnl
Improving MR image quality with a multi-task model, using convolutional losses.
BMC Medical Imaging
Attila Simkó, Simone Ruiter, Tommy Löfstedt, Anders Garpebring, Tufve Nyholm, Mikael Bylund, Joakim Jonsson
2023 — conf
Reproducibility of the Methods in Medical Imaging with Deep Learning.
MIDL
Attila Simkó, Anders Garpebring, Joakim Jonsson, Tufve Nyholm, Tommy Löfstedt
2022 J jnl
A Data-Adaptive Loss Function for Incomplete Data and Incremental Learning in Semantic Image Segmentation.
IEEE Trans. Medical Imaging
Minh H. Vu, Gabriella Norman, Tufve Nyholm, Tommy Löfstedt
2022 — conf
MRI bias field correction with an implicitly trained CNN.
MIDL
Attila Simkó, Tommy Löfstedt, Anders Garpebring, Tufve Nyholm, Joakim Jonsson
2022 J jnl
Region of Interest focused MRI to Synthetic CT Translation using Regression and Classification Multi-task Network.
CoRR
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
2022 J jnl
Reproducibility of the Methods in Medical Imaging with Deep Learning.
CoRR
Attila Simkó, Anders Garpebring, Joakim Jonsson, Tufve Nyholm, Tommy Löfstedt
2021 J jnl
A Data-Adaptive Loss Function for Incomplete Data and Incremental Learning in Semantic Image Segmentation.
CoRR
Minh H. Vu, Gabriella Norman, Tufve Nyholm, Tommy Löfstedt
2021 — conf
Changing the Contrast of Magnetic Resonance Imaging Signals using Deep Learning.
MIDL
Attila Tibor Simkó, Tommy Löfstedt, Anders Garpebring, Mikael Bylund, Tufve Nyholm, Joakim Jonsson
2021 J jnl
QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Metrics and Benchmarking Results.
CoRR
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
2020 J jnl
A Question-Centric Model for Visual Question Answering in Medical Imaging.
CoRR
Minh H. Vu, Tommy Löfstedt, Tufve Nyholm, Raphael Sznitman
2020 J jnl
A Question-Centric Model for Visual Question Answering in Medical Imaging.
IEEE Trans. Medical Imaging
Minh H. Vu, Tommy Löfstedt, Tufve Nyholm, Raphael Sznitman
2020 J jnl
Multi-Decoder Networks with Multi-Denoising Inputs for Tumor Segmentation.
CoRR
Minh H. Vu, Tufve Nyholm, Tommy Löfstedt
2020 — conf
Multi-decoder Networks with Multi-denoising Inputs for Tumor Segmentation.
BrainLes@MICCAI (1)
Minh H. Vu, Tufve Nyholm, Tommy Löfstedt
2019 J jnl
End-to-End Cascaded U-Nets with a Localization Network for Kidney Tumor Segmentation.
CoRR
Minh H. Vu, Guus Grimbergen, Attila Simkó, Tufve Nyholm, Tommy Löfstedt
2019 — conf
Ensemble of Streamlined Bilinear Visual Question Answering Models for the ImageCLEF 2019 Challenge in the Medical Domain.
CLEF (Working Notes)
Minh H. Vu, Raphael Sznitman, Tufve Nyholm, Tommy Löfstedt
2019 J jnl
Evaluation of Multi-Slice Inputs to Convolutional Neural Networks for Medical Image Segmentation.
CoRR
Minh H. Vu, Guus Grimbergen, Tufve Nyholm, Tommy Löfstedt
2019 — conf
TuNet: End-to-End Hierarchical Brain Tumor Segmentation Using Cascaded Networks.
BrainLes@MICCAI (1)
Minh H. Vu, Tufve Nyholm, Tommy Löfstedt
2019 J jnl
TuNet: End-to-end Hierarchical Brain Tumor Segmentation using Cascaded Networks.
CoRR
Minh H. Vu, Tufve Nyholm, Tommy Löfstedt
2008 — conf
Radiation therapy planning and simulation with magnetic resonance images.
Image-Guided Procedures
Thomas Boettger, Tufve Nyholm, Magnus Karlsson, Chandrasekhar Nunna, Juan Carlos Celi