| name | radiology-figure |
| description | Produce publication-quality white-background academic figures for Radiology (RSNA), Nature-portfolio/npj, European Radiology, NEJM, Science, or Lancet-family venues with Python (matplotlib): ROC curves, calibration plots, decision-curve analysis, forest/SROC plots, Kaplan-Meier curves with numbers-at-risk, Bland-Altman, heatmaps, radiogenomics plots, graphical/visual abstracts, and annotated imaging panels. Uses The Lancet Digital Health guide as the default Lancet-series proxy. Use when the user wants figures, plot cleanup, figure-set planning, journal-specific figure formatting, or overlap/crowding QA. Outputs editable vector (.svg/.pdf) plus 300+ dpi raster, enforces de-identification and journal typography, and never invents data points. |
Radiology Publication Figures
Use this skill to build figures that pass Radiology's technical and editorial bar: correct
file format and resolution, legible typography, color-blind-safe palettes, honest axes, and
the specific chart types imaging-AI reviewers expect (ROC, calibration, decision-curve,
forest/SROC, Kaplan-Meier, Bland-Altman), plus de-identified annotated imaging panels.
Core stance
- Vector first. Primary output is editable
.svg (or .pdf); secondary is a
≥ 300 dpi raster (TIFF/PNG). Keep text as text (svg.fonttype='none'), not outlines,
so editors can re-typeset.
- One figure, one message. Each panel answers one question; no two panels duplicate it.
Panels are labelled A, B, C (Radiology-family) or a, b, c (Nature-family — the case is
venue-dependent, never mixed within one manuscript; see "When to open extra files").
- Honest graphics. Axes start where the data demand (don't truncate to exaggerate);
show uncertainty (CI bands, error bars); state n.
- De-identify every image. No PHI burned into pixels, no faces/identifiers; scrub DICOM
overlays; report windowing (WL/WW) and add a scale bar where size matters.
- Match the journal. Sans-serif (Arial/Helvetica), figure width to column — Radiology-family
single ~85 mm / double ~170 mm, or Nature-family single 89 mm / double 183 mm (max height
170 mm) — adequate font size at final print size (≈ 7–9 pt min). Confirm the target venue
before sizing the first figure.
- Never fabricate data. Plot only supplied/loaded values; mark simulated/example data
clearly.
When to use
- Statistical figures: ROC (+ DeLong annotation), calibration, decision-curve, forest, SROC,
Kaplan-Meier (with numbers-at-risk), Bland-Altman, box/violin, heatmaps/clustermaps.
- Radiogenomics: MOFA/factor plots, deconvolution stacked bars, habitat maps, correlation
heatmaps.
- Imaging panels: multi-row montages, before/after, arrows/insets, windowing labels, scale
bars.
- Flow diagrams: CONSORT / STARD / PRISMA patient-selection diagrams.
When to open extra files
| File | Open when |
|---|
| references/radiology-figure-guidelines.md | File format, resolution, size, fonts, color, panel labelling, de-identification rules |
| references/chart-types.md | Choosing/parameterising the right statistical chart (ROC, calibration, DCA, forest, KM, Bland-Altman, heatmap) |
| references/imaging-panels.md | Building montages: windowing, arrows, insets, scale bars, anonymisation, panel layout |
| references/api.md | The matplotlib rcParams preamble, color palette, and reusable helper functions (ROC/calibration/forest/KM) |
| references/design-theory.md | Typography, layout grid, color-blind-safe palettes, anti-redundancy, accessibility |
| references/color-systems.md | Picking ONE palette (Okabe-Ito / NPG / Morandi) and mapping color→meaning so every figure matches |
| references/survival-figures.md | Kaplan-Meier integrity (curve ↔ numbers-at-risk ↔ censoring), numbers-at-risk done right, time-dependent (IPCW) ROC/calibration/DCA, incremental-value framing |
| references/figure-set-consistency.md | Unifying palette/fonts/axes across all figures, and cross-validating every figure number against the manuscript tables and data before export |
| references/nature-figure-spec.md | Target is a Nature-portfolio venue instead of Radiology — column widths (89/183 mm), lowercase panel letters, RGB, legend word cap, Extended Data/Source Data display-item split |
Workflow
- Confirm the target venue (Radiology-family default, or Nature-family →
nature-figure-spec.md) before sizing the first figure — column widths and panel-letter case
differ and are painful to change after the set is built.
- For venue-specific visual taste, open
journal-family-visual-style.md and apply the
target family's panel lettering, legend density, graphical abstract, table, and source-data
conventions.
- For full figure sets or layout-sensitive figures, open
figure-intent-and-render-qa.md and create the figure intent table plus source-data
crosswalk before drawing.
- Pick the chart for the message (chart-types.md). Discrimination → ROC; reliability →
calibration; clinical value → decision-curve; agreement → Bland-Altman; time-to-event →
Kaplan-Meier; meta-analysis → forest/SROC; whole-study summary → graphical abstract.
- Start the script with the rcParams preamble and palette from api.md.
- Build the panel(s) with helper functions; add CI bands, n, and clear axis labels with
units; label panels via
panel_letter()/add_panel_letter() (api.md) with the case set for
the confirmed venue — never hardcode chr(65+i) per script.
- For imaging panels, confirm de-identification, add windowing labels + scale bar +
arrows; keep grayscale unless color encodes data.
- Export
.svg (text-as-text) and a 300–600 dpi raster; check legibility at final
print width.
- QA (see contract) and inspect the final render for overlap/clipping before returning.
Output contract
Figure plan — what each panel shows and why; the chart type chosen.Figure intent / source-data crosswalk — for full figure sets or submission figures,
show what claim each panel supports and where the data came from.Script — a single runnable .py starting with the rcParams preamble; data inputs
clearly marked (real vs example).Files — figure.svg (primary) + figure.png/.tiff at ≥ 300 dpi.QA notes — fonts embedded as text, color-blind check, axis honesty, n shown,
de-identification confirmed for any image panel, final-size render checked for no
overlap/clipping, and venue-family visual style checked when applicable.
QA checklist (run before returning)
- rcParams preamble present; output is
.svg with svg.fonttype='none' and a ≥ 300 dpi
raster.
- Every axis labelled with units; legend present; panels labelled A/B/C or a/b/c per the
confirmed venue, consistently across the whole figure set.
- Uncertainty shown (CI band/error bars) and n stated.
- Color-blind-safe; not reliant on red/green alone; sufficient contrast.
- Imaging panels de-identified; windowing + scale bar present where relevant.
- No invented data points; example data flagged.
- Final exported render inspected at target size; no label/tick/legend/number overlap,
clipping, or text crossing plot elements.
- Venue-family rules satisfied when applicable (panel-letter case, background, legend length,
graphical abstract blocks, Source Data/table expectations).
Handoffs
- The statistic behind the plot (AUC CI, DeLong, ICC, calibration metrics, net benefit) →
radiology-stats.
- Whether the figure satisfies a checklist item (flow diagram for STARD/CONSORT), or the
Reporting Summary/Nature Portfolio checklist →
radiology-reporting.
- Figure legends/captions prose, display-item plan (main vs Extended Data) →
radiology-writing.
- Source Data files, Extended Data vs Supplementary Information wording →
radiology-data.
- Full figure set finished and ready for a harsh read before submission →
radiology-prereview.
