MICCAI 2026

What’s inside

• Starter files
• main.tex1.8 KB

  \documentclass[runningheads]{llncs}
  
  \usepackage{amsmath}
  \usepackage{booktabs}
  \usepackage{hyperref}
  
  \begin{document}
  
  \title{Your Paper Title Here}
  \titlerunning{Abbreviated Title}
  
  % Keep authors anonymized for submission; restore for camera-ready.
  \author{Anonymous Author(s)}
  \authorrunning{Anonymous}
  \institute{Anonymous Institution}
  
  \maketitle
  
  \begin{abstract}
  One paragraph summarizing the clinical problem, the imaging method, and the headline result. MICCAI abstracts should be self-contained.
  
  \keywords{Medical image computing \and Segmentation \and Deep learning}
  \end{abstract}
  
  \section{Introduction}
  Motivate the clinical problem and state the contribution. Prior segmentation methods address parts of the task~\cite{doe2024segmentation}, and recent work explores foundation models for medical imaging~\cite{smith2025foundation}.
  
  \section{Method}
  Describe the model and training objective:
  \begin{equation}
  \mathcal{L} = \mathcal{L}_{\mathrm{Dice}} + \lambda\, \mathcal{L}_{\mathrm{CE}},
  \label{eq:loss}
  \end{equation}
  where $\lambda$ balances the region and pixel terms.
  
  \section{Experiments}
  Describe datasets, splits, and metrics. Headline numbers go in Table~\ref{tab:results}.
  
  \begin{table}[htbp]
  \caption{Segmentation performance on the held-out test set.}
  \label{tab:results}
  \centering
  \begin{tabular}{lcc}
  \toprule
  Method & Dice (\%) & HD95 (mm) \\
  \midrule
  Baseline~\cite{doe2024segmentation} & 86.4 & 5.8 \\
  Ours & \textbf{89.1} & \textbf{4.2} \\
  \bottomrule
  \end{tabular}
  \end{table}
  
  \section{Conclusion}
  Recap the contribution, note limitations, and outline clinical next steps.
  
  This is a starter file. Ask the agent in the chat to draft sections, describe your method, or typeset your existing notes into this format.
  
  \bibliographystyle{splncs04}
  \bibliography{references}
  
  \end{document}
  

• Libraries and docs
• references.bib696 B

  @inproceedings{doe2024segmentation,
    author    = {Doe, Jane and Roe, Richard},
    title     = {Robust Organ Segmentation from Sparse Annotations},
    booktitle = {Medical Image Computing and Computer Assisted Intervention (MICCAI)},
    series    = {LNCS},
    volume    = {15001},
    year      = {2024},
    pages     = {101--111},
    publisher = {Springer}
  }
  
  @inproceedings{smith2025foundation,
    author    = {Smith, John and Lee, Ada},
    title     = {Foundation Models for Medical Image Analysis},
    booktitle = {Medical Image Computing and Computer Assisted Intervention (MICCAI)},
    series    = {LNCS},
    volume    = {15900},
    year      = {2025},
    pages     = {55--65},
    publisher = {Springer}
  }
  

• main.pdfprebuilt · 91 KBReplaced by the first recompile.

  Binary file, seeded as-is.

• main.synctex.gzprebuilt · 6.1 KBReplaced by the first recompile.

  Binary file, seeded as-is.