%\documentclass{midl} % Include author names
\documentclass[]{midl} % Anonymized submission
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% jmlr, amsmath, amssymb, natbib, graphicx, url, algorithm2e
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\usepackage[T1]{fontenc}
\usepackage{subfig}
%\usepackage{float}
\usepackage{booktabs}
\usepackage{mwe} % to get dummy images
\jmlrvolume{-- Under Review}
\jmlryear{2024}
\jmlrworkshop{Full Paper -- MIDL 2024 submission}
\editors{Under Review for MIDL 2024}
\usepackage[printonlyused,withpage]{acronym}
%\usepackage{subfig}
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\title[Test]{A sober recurrent  network for segmenting small object  applied to thrombus localization in brain \acs{mri}}
\title[A recurrent  network for segmenting the thrombus ]{A recurrent  network for segmenting the thrombus on brain \acs{mri} in patients with hyper-acute ischemic stroke }

 % Use \Name{Author Name} to specify the name.
 % If the surname contains spaces, enclose the surname
 % in braces, e.g. \Name{John {Smith Jones}} similarly
 % if the name has a "von" part, e.g \Name{Jane {de Winter}}.
 % If the first letter in the forenames is a diacritic
 % enclose the diacritic in braces, e.g. \Name{{\'E}louise Smith}

 % Two authors with the same address
\midlauthor{\Name{Sofia Vargas-Ibarra\nametag{$^{1}$}} \Email{sofia.vargasibarra@univ-evry.fr} \\ 
\Name{Vincent Vigneron\nametag{$^{1}$}} \Email{vincent.vigneron@univ-evry.fr}\\ 
\Name{Hichem Maaref\nametag{$^{1}$}} \Email{hichem.maaref@univ-evry.fr}\\
\addr  $^{1}$Univ Evry, Université Paris-Saclay, IBISC, Evry, France.
 \AND
 \Name{Sonia Garcia-Salicetti\nametag{$^{2}$}} \Email{sonia.garcia@telecom-sudparis.eu}\\
\addr $^{2}$T\'el\'ecom SudParis, Institut Polytechnique de Paris, Evry, France.
   \AND
   \Name{Jonathan Kobold\nametag{$^{3}$}} \Email{jonathan.Kobold@gmx.de}\\
\addr $^{3}$Hensoldt Analytics, Munich, Germany.
   \AND
   \Name{Nicolas Chausson\nametag{$^{4}$}} \Email{nicolas.chausson@chsf.fr}\\
   \Name{Didier Smadja\nametag{$^{4}$}} \Email{didier.smadja@chsf.fr}\\ 
\Name{Yann Lhermitte\nametag{$^{4}$}} \Email{yann.lhermitte@chsf.fr}\\
   \addr $^{4}$Neurology Department, Sud-Francilien Hospital, Corbeil-Essonnes, France.}

% \Name{Author Name2} \Email{xyz@sample.edu}\\
% \addr Address 2

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 % \midlauthor{\Name{Author Name1} \Email{an1@sample.edu}\\
 %  \Name{Author Name2} \Email{an2@sample.edu}\\
 %  \Name{Author Name3} \Email{an3@sample.edu}\\
 %  \addr Address}


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% \midlauthor{\Name{Author Name1} \Email{abc@sample.edu}\\
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% \AND
% \Name{Author Name2} \Email{xyz@sample.edu}\\
% \addr Address 2
% }

%\footnotetext[1]{Contributed equally}

% More complicate cases, e.g. with dual affiliations and joint authorship

   
\begin{document}

\input{files/acronyms}

\maketitle

\begin{abstract}
In the stroke workflow, timely decision-making is crucial. Identifying, localizing, and measuring occlusive arterial thrombi during initial imaging is a critical step that triggers the choice of therapeutic treatment for optimizing vascular re-canalization. We present a recurrent model that segments the thrombus in patients suffering from a hyper-acute stroke. A cross-attention module is defined to merge the diffusion and susceptibility-weighted modalities available in \ac{mri}, which are fed to a modified version of \ac{clstm}. It detects almost all the thrombi with a Dice higher than 0.6. The lesion segmentation prediction reduces the false positives to almost zero and the performance is comparable between distal and proximal occlusions. 
\end{abstract}

\begin{keywords}
hyperacute stroke, brain imagery, MRI modalities, lesion, thrombus, spatial recurrence, deep learning
\end{keywords}
\input{files/definitions}

%\tableofcontents


\section{Introduction}
\input{files/introv2}


\section{Materials and methods}
\input{files/materials.tex}

\input{files/method}



\section{Results}
\input{files/experimentsv2}

\section{Conclusion}
\input{files/conclusion}

\newpage
\bibliographystyle{ieeetr}
\bibliography{files/bib.bib}

\end{document} oki