Agent Skillsbrycewang-stanford/Awesome-Journal-Skills › medical-image-computing-and-computer-assisted-intervention

medical-image-computing-and-computer-assisted-intervention

GitHub

针对MICCAI会议投稿的适配与重构工具,评估医学图像AI论文契合度、证据强度及拒稿风险,指导从期刊/预印本向CS会议叙事转型。

Computer-Science-Conference-Skills/skills/medical-image-computing-and-computer-assisted-intervention/SKILL.md brycewang-stanford/Awesome-Journal-Skills

Trigger Scenarios

作者指定MICCAI为目标会议 需评估医学图像分析稿件的会议适配性 需将论文从期刊或arXiv风格重构为CS会议叙事 需要诊断证据缺口、匿名性或反驳策略

Install

npx skills add brycewang-stanford/Awesome-Journal-Skills --skill medical-image-computing-and-computer-assisted-intervention -g -y
More Options

Non-standard path

npx skills add https://github.com/brycewang-stanford/Awesome-Journal-Skills/tree/main/Computer-Science-Conference-Skills/skills/medical-image-computing-and-computer-assisted-intervention -g -y

Use without installing

npx skills use brycewang-stanford/Awesome-Journal-Skills@medical-image-computing-and-computer-assisted-intervention

指定 Agent (Claude Code)

npx skills add brycewang-stanford/Awesome-Journal-Skills --skill medical-image-computing-and-computer-assisted-intervention -a claude-code -g -y

安装 repo 全部 skill

npx skills add brycewang-stanford/Awesome-Journal-Skills --all -g -y

预览 repo 内 skill

npx skills add brycewang-stanford/Awesome-Journal-Skills --list

SKILL.md

Frontmatter
{
    "name": "medical-image-computing-and-computer-assisted-intervention",
    "description": "Use when targeting International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) or deciding whether a computer-science manuscript fits this venue. Encodes conference fit, framing, evidence bar, submission-cycle checks, rebuttal posture, and desk-reject risks for medical imaging AI."
}

International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI)

Conference positioning

International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) is a top computer-science conference venue for medical image analysis, image-guided intervention, computational anatomy, and clinical AI validation. It rewards a medical imaging paper with clinical-task grounding, robust validation, and careful claims about utility. Treat this skill as a fit / venue-selection / re-framing tool for conference submission strategy, not as a substitute for the current year's CFP, author kit, ethics policy, or submission portal.

Because CS conferences change deadlines, templates, page limits, review workflow, artifact rules, AI-use policy, and rebuttal formats every cycle, always verify the live official instructions before making a submission-ready recommendation. Start from the official source anchor recorded for this venue in ../../resources/conference-roster.md and ../../resources/official-source-map.md.

When to trigger

  • The author names MICCAI / International Conference on Medical Image Computing and Computer Assisted Intervention as the target venue.
  • A manuscript in medical image analysis needs a conference-fit read before being formatted or submitted.
  • The paper must be re-framed from journal style or arXiv style into a selective CS conference narrative.
  • The author needs an evidence-gap, anonymity, artifact, rebuttal, or re-routing diagnosis for this venue.

Scope & topic fit

  • Core fit: medical image analysis, image-guided intervention, computational anatomy, and clinical AI validation.
  • Best submissions make a precise contribution type visible: algorithm, theorem, system, dataset, benchmark, empirical finding, design artifact, tool, or socio-technical analysis.
  • The paper should explain why the result matters to MICCAI's reviewers, not just why it is interesting to the authors' lab or product context.
  • Position related work against the most recent conference-cycle papers in this venue and its closest siblings; stale comparisons are a common early-review weakness.
  • If the contribution is interdisciplinary, state which part is CS research and which part is domain evidence.

Venue-specific calibration

  • Reviewer lens: Treat MICCAI as a medical imaging AI venue whose reviewers expect the scope and evidence to match its own community. Do not submit a generic CS paper until the introduction names the exact subcommunity, contribution type, and proof or empirical standard.
  • Contribution hook to foreground: the venue-specific contribution bar.
  • Scope vocabulary to use naturally in the abstract and introduction: medical image analysis, image-guided intervention, computational anatomy, and clinical AI validation.
  • Distinctive fingerprint for reviewer calibration: medical, image, analysis, image-guided, intervention, computational, anatomy, clinical, validation, venue-specific, contribution, imaging, miccai.
  • Official anchor domain: www.miccai.org. Quote annual rules only after opening that source and the current-year CFP/author kit.

Close-neighbor routing guardrail

  • Use this profile only when the manuscript's central contribution is genuinely in medical imaging AI and the author can say why MICCAI reviewers are the primary audience, not merely a convenient deadline.
  • Closest roster neighbors to compare before final routing: acm-conference-on-fairness- accountability-and-transparency (FAccT), european-conference-on-artificial-intelligence (ECAI), conference-on-computational-natural-language-learning (CoNLL), conference-on- robot-learning (CoRL). Break ties by contribution type, evidence shape, reviewer community, and the current official CFP from www.miccai.org.

Method & evidence bar

  • Use current vision baselines, strong ablations, dataset-specific protocols, and qualitative examples that reveal failure modes.
  • Keep the anonymous submission self-contained; external material should follow the current-cycle policy exactly.
  • For generated or foundation-model outputs, show robustness, data provenance, and evaluation beyond cherry-picked visuals.
  • For MICCAI, the evidence must support the venue-specific signature: a medical imaging paper with clinical-task grounding, robust validation, and careful claims about utility.
  • Include limitations, negative results, compute/resource reporting, data provenance, and ethics details when they affect the claim.

Structure & house style

  • Lead with the visual problem and the technical insight; then prove it across datasets, metrics, and ablations.
  • Make figures do work: pipeline, qualitative wins/failures, and compact quantitative comparisons.
  • Use the current official template exactly; do not guess page limits, font sizes, supplement rules, anonymity exceptions, or camera-ready requirements from old cycles.
  • The introduction should answer: problem, why now, what is new, why this venue, and what evidence proves the claim.
  • Put the strongest result in the main paper, not only in the appendix or supplement; reviewers should not have to reconstruct the contribution.

Official-cycle checklist

  • Open the live official venue page: https://www.miccai.org/
  • Re-check the current cycle's CFP, author kit, submission system, abstract/paper deadlines, page limits, supplementary-material rules, anonymity policy, dual-submission policy, ethics policy, AI-use policy, artifact/code/data expectations, rebuttal/author-response format, and camera-ready requirements.
  • Confirm the review workflow and portal: OpenReview / CMT / HotCRP / PCS / START or society portal, as specified for the current cycle.
  • Check whether accepted papers require in-person presentation, separate registration, artifact badges, proceedings copyright, or post-acceptance release forms.
  • If the live official instructions conflict with this skill, the official instructions win.

Pre-submission self-check

  • One sentence states why this manuscript belongs at MICCAI, using the venue's scope rather than generic "top conference" language.
  • The claim is calibrated to the evidence: no broader than the datasets, proofs, systems, user studies, deployments, or threat model support.
  • Related work includes the nearest current-cycle medical imaging AI papers and explains the technical delta.
  • The paper satisfies the current official template, anonymity, ethics, artifact, and rebuttal requirements.
  • The main paper is self-contained enough for reviewers to evaluate novelty and correctness without hunting through external links.

Common desk-reject triggers

  • A thin architecture tweak with marginal gains and no analysis.
  • Using non-comparable baselines, private data splits, or hidden external links that violate review policy.
  • Ethics, consent, or biometric/medical claims handled as boilerplate rather than as real constraints.
  • Formatting, anonymity, dual-submission, external-link, or supplement violations under the current-year policy.
  • A contribution framed for a neighboring field while giving MICCAI reviewers too little technical or empirical substance.

Re-routing decision

If the paper misses MICCAI's bar, compare against computer-vision-and-pattern-recognition / international-conference-on-computer-vision / european-conference-on-computer-vision / winter-conference-on-applications-of-computer-vision. Re-route based on contribution type, not prestige: theory to a theory venue, systems to a systems venue, application-heavy work to a domain venue, and early ideas to workshops or shorter tracks when the official CFP supports them.

Output format

[Fit] High / Medium / Low (one-line reason)
[Target] International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI)
[Contribution type] algorithm / theory / system / dataset / benchmark / empirical / design / security / other
[Main evidence gap] <single most important missing proof, experiment, study, artifact, or policy check>
[Official items to re-check] CFP / author kit / deadline / format / anonymity / ethics / AI-use / artifact / rebuttal / camera-ready
[Top rejection risk] <venue-specific risk>
[Re-route suggestion] <better-matched conference or journal if not a fit>

Version History

  • 1839142 Current 2026-07-05 12:46

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