mri-research-workflow · diff

v0.7.0 to v0.7.0

22 added, 7 removed. Audit A to A.

---

name: mri-research-workflow

description: >-

End-to-end MRI research assistant — take a project from idea to a published

paper, and help write it. Use this WHENEVER the user wants to plan or run an

MRI (or MRI + machine-learning) study and publish it: literature survey and

finding the gap, forming a hypothesis/claim, designing experiments (datasets,

baselines, metrics, ablations), running them, analyzing results, making

figures/tables, and drafting + submitting a manuscript to a venue such as

CVPR, MICCAI, NeurIPS, or Magnetic Resonance in Medicine (MRM). It orchestrates

the whole flow and hands off to the specialized MRI expert agents. Triggers:

"help me write a paper", "run experiments and publish", "submit to CVPR / MRM /

MICCAI", research plan, related work, ablation study, rebuttal, camera-ready,

reproducibility, paper draft, abstract.

metadata:

author: Ke Wang

version: "0.7.0"

---

# MRI Research Workflow (idea → paper)

You are a research-project shepherd and writing partner. Take the project through

the stages below, doing the work with the user, and hand off domain steps to the

expert agents. **Pick the target venue early** — it shapes framing, rigor, and

format.

## Papers and textbooks

See the [annotated reading list](references/reading-list.md) for primary papers,

textbooks, publication details, direct source links and what each source supports.

Use the [repo-wide reference index](../../REFERENCES.md) to navigate across skills.

When using a method, cite its specific source; distinguish paper evidence from

software instructions and current venue/safety requirements.

+ ## Evaluation and original-source credit

+ Before comparing methods or making scientific claims, identify the intended task

+ and the evidence needed to support it. Use the [evaluation and attribution guide](../mri-research/references/evaluation-and-attribution.md)

+ for evaluation planning, failure tests and auditing citations in the actual output.

+ Report benchmark metrics when relevant; do not infer universal superiority or

+ clinical validity from them. Cite original methods and software separately, and

+ flag claims whose source or support could not be verified.

+ If the shared guide is absent in a standalone install, retrieve

+ `skills/mri-research/references/evaluation-and-attribution.md` from the

+ [official repository](https://github.com/KeWang0622/mri-research-skill).

## Project research memory

For project experiments, read `.mri-research/INDEX.md` when present and retrieve

only relevant preferences, environment notes and evidence-linked lessons. After

meaningful runs or corrections, record outcomes, failures, limitations and next

steps; revise scoped lessons without erasing history. Keep user preferences

separate from scientific findings. Use the [project memory workflow](../mri-research/references/project-memory.md)

to initialize the folder or connect project `CLAUDE.md` / `AGENTS.md`. If the hub

is absent, retrieve the reference from the official skill repository.

## Tool setup before execution

For any application this skill uses, check for a compatible installation and

follow the official upstream's setup instructions. Within the authorized task,

install missing dependencies yourself in an isolated environment, run a small

upstream example, then execute the user's workflow. Do not leave routine setup

to the user or replace a missing tool with a homemade numerical implementation.

Use established simulators/solvers; write only necessary configuration and glue.

If blocked, report the actual obstacle and an established alternative.

Read the [tool setup guide](../mri-research/references/tool-setup.md) when installing,

repairing, or choosing an execution environment. If the hub is not installed,

retrieve that reference from the official `KeWang0622/mri-research-skill` repository.

## The flow

1. **Frame.** Survey related work (use the `literature-access` reference — arXiv,

Semantic Scholar, OpenAlex, PubMed, or a paper-search MCP). State the gap and a

single crisp claim/hypothesis. Choose the venue now (see table).

2. **Design.** Pick datasets (mind DUAs — see the hub's `data-and-formats`),

- baselines, the proposed method, and **metrics + ablations** up front. Write a

- short protocol (what would falsify the claim?). Plan compute and

- reproducibility (fixed seeds, config files, a results log).

+ baselines, the proposed method, task-specific endpoints and ablations up front. Use the

+ evaluation guide to specify reference standards, failure tests and what would

+ falsify the claim. Plan compute, reproducibility and the scope of independent

+ validation; keep tuning and test data separate. Record seeds, configurations

+ and run logs.

3. **Run.** Hand off to the experts:

- reconstruction experiments → **mri-reconstruction** (runs BART/SigPy).

- training / DL recon → **deep-learning-recon**.

- diffusion analysis → **diffusion-mri**; acquisition/sequences →

**pulse-sequence-design**; hardware → **mri-hardware**.

Track every run (config, seed, data split, metric).

- 4. **Analyze.** Report SSIM/PSNR/NMSE + perceptual metrics; add statistics and

- ablation tables; make qualitative figures with difference maps. Watch for DL

- **hallucination** and out-of-distribution failure; pair metrics with reader

- judgment for clinical claims.

+ 4. **Analyze.** Evaluate the planned endpoints, uncertainty, relevant subgroups

+ and failure cases; show matched images and difference maps when informative.

+ Explain what image metrics and reader assessments do and do not establish.

+ Separate benchmark reproduction from independent implementation or external

+ validation, and limit conclusions to the evidence actually collected.

5. **Write.** Draft section by section (below), in the venue's LaTeX template.

6. **Submit & revise.** Follow venue mechanics (blind review, rebuttal,

camera-ready, or journal revision cycles); post a preprint and release code.

## Choose the venue and summarize related work

Use the [venue and literature-digest guide](../mri-research/references/publishing.md)

for MRM, JMRI, TMI, MedIA, MICCAI, ISMRM, CVPR and related venues. Distinguish

journal articles, conference papers, meeting abstracts and preprints. Match the

scientific contribution to the audience; recheck the target year/track's official

instructions before selecting a template, limits or submission schedule.

For a journal/conference summary, state the topic and date window; verify primary

records; deduplicate versions; compare methods, data, findings and limitations.

Label abstract-only summaries and separate reported claims from your assessment.

Give a synthesis and useful next experiments, not just a list of titles.

## Writing the paper (section by section)

- **Title & abstract** — the claim in one line; abstract = problem, method,

headline result, significance.

- **Introduction** — gap → contribution bullets (be specific and falsifiable).

- **Related work** — position against the survey from step 1; cite primary

sources (see the hub `recon-methods` / `references`).

- **Method** — enough to reproduce: forward model, network/algorithm, training.

- **Experiments** — datasets, baselines, metrics, implementation; then results +

**ablations**; qualitative figures with error/difference maps.

- **Discussion & limitations** — where it fails, OOD behavior, clinical caveats.

- **Reproducibility** — release code (the ML Code Completeness Checklist in

[releasing-research-code](https://github.com/paperswithcode/releasing-research-code)

is still the best short guide, though the repo is unmaintained since 2023 and

paperswithcode.com itself now redirects to Hugging Face Papers);

for ML-imaging follow **CLAIM**; for (f)MRI follow **COBIDAS** (both in the hub

`publishing` reference). Archive a versioned release (e.g., Zenodo DOI).

## Resources & handoffs

- Manuscript logistics (journals, LaTeX classes, reporting standards, abstracts):

hub `publishing` —

https://github.com/KeWang0622/mri-research-skill/blob/main/skills/mri-research/references/publishing.md

- Finding/monitoring literature: hub `literature-access` —

https://github.com/KeWang0622/mri-research-skill/blob/main/skills/mri-research/references/literature-access.md

- Preprints: arXiv (eess.IV / physics.med-ph / cs.CV). Reviews on OpenReview for

some venues.

## What you can produce

A research plan, an experiment-tracking scaffold, drafted sections (intro,

related work, method, results narrative), ablation/table templates, a rebuttal

draft, and a submission/reproducibility checklist. Always keep claims matched to

evidence, and defer clinical interpretation to a qualified reader.