\subsection{Dataset and preprocessing}


Two datasets are used in this study: CHSF (proximal occlusions (P)) and  MATAR (distal occlusions (D)). All \acp{mri} come from patients treated for stroke at the Centre Hospitalier Sud-Francilien and were acquired from a 1.5 T and a 3 T GE Healthcare \ac{mri} machine in the hyper-acute phase, before treatment. 
The details of datasets are described in Table \ref{tab:complete_dataset}.
\begin{wraptable}{l}{8cm}
\vspace*{-0.3in}
\centering
\floatconts
  {tab:complete_dataset}%
  {\caption{Dataset description. The sizes are in pixels (pix.) and the average (avg) of the  ground-truths sizes are provided   }}
  {  \vspace*{-0.2in}
\scalebox{0.7}{\begin{tabular}{lcc}
    \toprule
     &CHSF & MATAR\\
    \midrule


    Age (years)  & 74.33  $\pm$ 0.74&72.95 	$\pm$ 1.6 \\
    Male  & 43.3$\%$ & 46.5$\%$   \\
    Hypertension  & 62$\%$ & 59$\%$\\
    Current smokers  &11$\%$  & 13$\%$ \\
    %Initial NIHSS  &  4.9$\pm$0.51 &\\
    DWI-ASPECTS\footnotemark  & 3.69 (0-10) & 9 (7.75-10)\\
    
    SWAN slices &72 to 216 & 72 to 232 \\
    DWI slices &24 to 38 &  24 to 40  \\
    SWAN shape (pix. per slice) & 512$\times$512&  512$\times$512\\
    DWI shape (pix. per slice) &  256$\times$256& 256$\times$256\\
    Thrombi size (mm$^{3}$) &231.97 & 77.04\\
        Lesion size (mm$^{3}$) &31770.21 & 5010.15\\
    Number of patients & 63& 125 \\

    \bottomrule
    \end{tabular}}}
\end{wraptable}
\footnotetext{It measures the extent of early ischemic changes in anterior circulation hyperacute ischemic stroke. A point is subtracted if it touches one of the 10 brain divisions}
Even though they have been used for several clinical studies \cite{chsf}, we use only a subset of it, segmented by neurologists. Notice the differences between MATAR and CHSF: the thrombi and lesion size and the ASPECT.  Due to registration problems such as missing modalities, only 188 \acp{mri} are used finally. The susceptibility-weighted angiography (SWAN) with its associated PHASE are used to segment the thrombi, and the apparent diffusion coefficient (ADC), and diffusion-weighted imaging (DWI) modalities are used to segment the lesion. The susceptibility images (SWAN and PHASE) have the same geometries and alignment. This is because SWAN is calculated using the machine's PHASE and the magnitude image. It happens the same for the diffusion ones, as ADC is obtained from DWI and B0.

The dataset is normalized using Nyul's method \cite{nyul}. Computing per modality an average histogram using the quantiles of all the data,  the MRI's intensities are normalized using that histogram as a reference. The skull-stripped \ac{mri}s are used and DWI is coregistered to SWAN using ANTS software, producing images of size 512$\times$512 in the ($x$,$y$)-plane and $z$ varies between patients. As input for the model, we take  256$\times$256$\times s$-size crops, where $s$ is the chosen number of slices. To reduce $x$ and $y$ the center of mass is calculated to add around 128 pixels in all dimensions (arriving at a size of 256$\times$256 around that center). As DWI and SWAN have different resolutions and indeed the lesion is normally a bigger region than the thrombi, the crops in $z$ are done in the original resolution, taking the corresponding slices. Having $s$ slices from SWAN and  $s$ slices from DWI means that we are seeing a bigger brain region in the diffusion modality, which allows the model to have an increased attention impact.

