\documentclass{midl} 
% Include author names

% The following packages will be automatically loaded:
% jmlr, amsmath, amssymb, natbib, graphicx, url, algorithm2e
% ifoddpage, relsize and probably more
% make sure they are installed with your latex distribution
% \usepackage[ruled,vlined]{algorithm2e}
\jmlryear{2026}
\jmlrworkshop{Full Paper -- MIDL 2026}
\jmlrvolume{-- 209}
\editors{Accepted for publication at MIDL 2026}
\usepackage{mwe} % to get dummy images
\usepackage{float}


% \title[INFORM-CT]{INFORM-CT: \textbf{In}tegrating LLMs and VLMs \textbf{for} Incidental Findings \textbf{M}anagement in Abdomen CT}
\title[INFORM-CT]{INFORM-CT: \textbf{IN}tegrating LLMs and VLMs \textbf{FOR} Incidental Findings \textbf{M}anagement in Abdominal CT}
% \title[A BRIF]{A BRIF: Agentic approach for BRidging LLMs and VLMs for Incidental Findings management in Abdomen CT}
 % 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{Author Name1} \Email{abc@sample.edu}\and
 %  \Name{Author Name2} \Email{xyz@sample.edu}\\
 %  \addr Address}

 % Three or more authors with the same address:
 % \midlauthor{\Name{Author Name1} \Email{an1@sample.edu}\\
 %  \Name{Author Name2} \Email{an2@sample.edu}\\
 %  \Name{Author Name3} \Email{an3@sample.edu}\\
 %  \addr Address}


% Authors with different addresses:
% \midlauthor{\Name{Author Name1} \Email{abc@sample.edu}\\
% \addr Address 1
% \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
\midlauthor{
\Name{Idan Tankel\midljointauthortext{Contributed equally}\nametag{$^{1}$}}  \\
\addr $^{1}$ GE Healthcare Technology and Innovation Center, Niskayuna, USA \\
\Name{Nir Mazor\midlotherjointauthor\nametag{$^{1}$}} \\
\Name{Rafi Brada\nametag{$^{1}$}} \\
\Name{Christina Lebedis\nametag{$^{2}$}} \orcid{0000-0002-8849-736X} \\
\addr $^{2}$ Boston Medical Center, Boston, USA \\
\Name{Guy Ben-Yosef\midljointauthortext{Contributed equally}\midljointauthortext{Corresponding Author}\nametag{$^{1}$}} \orcid{0000-0002-4368-0750} \\
% \addr $^{4}$ Address 4
}

\begin{document}

\maketitle

\begin{abstract}

Incidental findings in CT scans, though often benign, can have significant clinical implications and should be reported according to established guidelines. Traditional manual inspection by radiologists is time-consuming and subject to variability.

This paper proposes a novel framework that leverages large language models (LLMs) and foundational vision–language models (VLMs) within a plan-and-execute agentic architecture to improve the efficiency and precision of incidental-findings detection, classification, and reporting in abdominal CT scans. Given medical guidelines for abdominal organs, the management process is automated through a planner–executor framework. The planner, based on an LLM, generates Python scripts from predefined base functions, while the executor runs these scripts to perform the required detections and evaluations using VLMs, segmentation models, and image-processing subroutines.

We demonstrate the effectiveness of our approach through experiments on a CT-abdominal benchmark covering three organs, in a fully automatic end-to-end setup. Our results show that the proposed framework outperforms existing purely VLM-based approaches in both accuracy and efficiency. Implementation details and code are available at \href{https://anonymous.4open.science/r/InformCT_public-8A77/README.md}{this
 repository}.

% \keywords{Incidental Findings Detection \and Abdominal CT \and Vision-Language Models \and Planner-Executor Framework \and Clinical Guidelines}


\end{abstract}

\begin{keywords}
Incidental Findings Detection, Abdominal CT, Vision-Language Models, Planner-Executor Framework, Clinical Guidelines
\end{keywords}

% \section{Introduction}

\input{sections/intro}

% \input{miccai_2025/sections/related_work}

\input{sections/methods}

\input{sections/exps}


\input{sections/discussion}



\newpage

% This is where the content of your paper goes.  Some random
% notes\footnote{Random footnote are discouraged}:
% \begin{itemize}
% \item You should use \LaTeX \cite{Lamport:Book:1989}.
% \item JMLR/PMLR uses natbib for references. For simplicity, here, \verb|\cite|  defaults to
%   parenthetical citations, i.e. \verb|\citep|. You can of course also
%   use \verb|\citet| for textual citations.
% \item Eprints such as arXiv papers can of course be cited \cite{Hinton:arXiv:2015:Distilling}. We recomend using a \verb|@misc| bibtex entry for these as shown in the sample bibliography.
% \item You should follow the guidelines provided by the conference.
% \item Read through the JMLR template documentation for specific \LaTeX
%   usage questions.
% \item Note that the JMLR template provides many handy functionalities
% such as \verb|\figureref| to refer to a figure,
% e.g. \figureref{fig:example},  \verb|\tableref| to refer to a table,
% e.g. \tableref{tab:example} and \verb|\equationref| to refer to an equation,
% e.g. \equationref{eq:example}.
% \end{itemize}

% \begin{table}[htbp]
%  % The first argument is the label.
%  % The caption goes in the second argument, and the table contents
%  % go in the third argument.
% \floatconts
%   {tab:example}%
%   {\caption{An Example Table}}%
%   {\begin{tabular}{ll}
%   \bfseries Dataset & \bfseries Result\\
%   Data1 & 0.12345\\
%   Data2 & 0.67890\\
%   Data3 & 0.54321\\
%   Data4 & 0.09876
%   \end{tabular}}
% \end{table}


% \begin{algorithm2e}
% \caption{Computing Net Activation}
% \label{alg:net}
%  % older versions of algorithm2e have \dontprintsemicolon instead
%  % of the following:
%  %\DontPrintSemicolon
%  % older versions of algorithm2e have \linesnumbered instead of the
%  % following:
%  %\LinesNumbered
% \KwIn{$x_1, \ldots, x_n, w_1, \ldots, w_n$}
% \KwOut{$y$, the net activation}
% $y\leftarrow 0$\;
% \For{$i\leftarrow 1$ \KwTo $n$}{
%   $y \leftarrow y + w_i*x_i$\;
% }
% \end{algorithm2e}

\clearpage  % Acknowledgements, references, and appendix do not count toward the page limit (if any)
% Acknowledgments---Will not appear in anonymized version
% \midlacknowledgments{We thank a bunch of people.}


\bibliography{midl26_209}


\appendix
\input{sections/appendix}



% This is a boring technical proof of
% \begin{equation}\label{eq:example}
% \cos^2\theta + \sin^2\theta \equiv 1.
% \end{equation}

% \section{Proof of Theorem 2}

% This is a complete version of a proof sketched in the main text.

\end{document}
