Imaging Evidence Path
A practical advanced self-study guide for one learner — physician and senior software engineer — moving into medical imaging, quantitative imaging, radiomics, clinically rigorous ML, and imaging informatics.
The chapters
Section titled “The chapters”| # | Chapter | Focus |
|---|---|---|
| 1 | CT and DICOM | HU, slope/intercept, hierarchy, identifiers |
| 2 | Geometry, segmentation and resampling | IOP/IPP, FoR, SEG, masks |
| 3 | Quantitative imaging and radiomics | features, IBSI, robustness |
| 4 | Statistical learning and validation | leakage, calibration, survival |
| 5 | Imaging informatics | PACS, DICOMweb, IHE |
| 6 | Medical imaging AI | segmentation, synthesis, foundation models |
| 7 | Research methodology | reading and designing imaging studies |
| 8 | MRI and multimodality foundations | T1/T2, sequences, DWI, k-space |
| 9 | Clinical deployment, human-AI, lifecycle | reader studies, drift, monitoring |
Plus the 3D Slicer companion (Jan Witowski course bridge).
Where to find things
Section titled “Where to find things”- Literature map — the intellectual map of the literature (PMIDs/DOIs; PDFs live in Zotero).
- Courses & videos — selected external instruction, bridged not duplicated.
- Standards & reference — DICOM, SimpleITK, 3D Slicer, IBSI, PyRadiomics, CLAIM/TRIPOD+AI.
- TRACE-CT learning map — real worked examples from the driving laboratory.
- EuSoMII 2026 note — MSK and generalist imaging AI.
If you have 60 minutes tonight
Section titled “If you have 60 minutes tonight”Pick one: open a RIDER slice in pydicom and convert stored pixels to HU (Ch. 1); compute a real series’ slice normal (Ch. 2); continue the ISLP chapter (Ch. 4); or dissect Tran et al. through the research-methodology lens. Depth over breadth.
This reader renders the repository’s canonical Markdown directly — it does not duplicate it. The source of truth is
BioMedical-IT/imaging-evidence-pathon Forgejo.