\documentclass{midl} 

\jmlryear{2026}
\jmlrworkshop{Full Paper -- MIDL 2026}
\jmlrvolume{-- nnn}
\editors{Accepted for publication at MIDL 2026}

\title[MedFuncta: A Unified Framework for Learning Efficient Medical Neural Fields]{MedFuncta: A Unified Framework for Learning Efficient Medical Neural Fields}

\input{sections/00_preamble}

\midlauthor{\Name{Paul Friedrich\nametag{$^{1}$}} \orcid{0000-0003-3653-5624} \Email{paul.friedrich@unibas.ch}\\
\Name{Florentin Bieder\nametag{$^{1}$}} \orcid{0000-0001-9558-0623} \Email{florentin.bieder@unibas.ch}\\
\Name{Julian McGinnis\nametag{$^{2}$}} \orcid{0009-0000-2224-7600} \Email{julian.mcginnis@tum.de}\\
\Name{Julia Wolleb\nametag{$^{3}$}} \orcid{0000-0003-4087-5920} \Email{julia.wolleb@yale.edu}\\
\Name{Daniel Rueckert\nametag{$^{2,4}$}} \orcid{0000-0002-5683-5889} \Email{daniel.rueckert@tum.de}\\
\Name{{Philippe C.} Cattin\nametag{$^{1}$}} \orcid{0000-0001-8785-2713} \Email{philippe.cattin@unibas.ch}\\
\addr $^{1}$ Department of Biomedical Engineering, University of Basel, Switzerland\\
\addr $^{2}$ Institute of Artificial Intelligence in Medicine, Technical University of Munich, Germany\\
\addr $^{3}$ Department of Biomedical Informatics and Data Science, Yale University, USA\\
\addr $^{4}$ Department of Computing, Imperial College London, UK
}

\begin{document}

\maketitle

\input{sections/01_abstract}  
\input{sections/02_introduction}
\input{sections/04_method}
\input{sections/05_experiments}
\input{sections/06_dataset}
%\input{sections/07_limitations}
\input{sections/08_discussion}


\midlacknowledgments{This work was financially supported by the Werner Siemens Foundation through the MIRACLE II project. JM is supported by Bavarian State Ministry for Science and Art (Collaborative Bilateral Research Program Bavaria – Québec: AI in medicine, grant F.4-V0134.K5.1/86/34). JW is funded by the Swiss National Science Foundation
(Grant No. P500PT\_222349)}
\bibliography{midl26_8}

\appendix
\input{sections/03_relatedwork}
\input{sections/09_appendix}
\end{document}