Interactive orthopaedic education
Imaging · Projection Anatomy

3D Radiograph Lab

Choose an anatomy module, learn how its views are obtained, judge whether a film is technically adequate, and connect 2D landmarks to the structures that create them.

Educational use only

OrthoAnimate modules demonstrate concepts and support teaching. They are not validated patient-specific planning or clinical decision-support systems.

PreviewVersion 0.4.7Updated

Start here

Select an anatomy tag, choose a projection, then rotate the 3D model while comparing it with the attenuation-based digitally reconstructed radiograph (DRR).

Open interactive workspace
What you’ll learn 3 objectives
  • Relate 2D projection landmarks to their 3D anatomical origins.
  • Describe how common pelvis, hip, and lumbar-spine views are obtained.
  • Recognise technical adequacy and common positioning errors.

This is a resident teaching model with editable assumptions and explicit limitations. It is not patient-specific and must not guide clinical decisions.

The left viewport shows an interactive CT-derived 3D anatomical model. The right viewport shows the corresponding attenuation-based simulated radiograph. Projection-specific acquisition guidance, quality criteria, purpose, landmarks, and measurements appear in the controls.

Preparing interactive scanFinding the anatomy package…This may take several seconds on the first visit.
2%
3D anatomy Smoothed surface
Opacity 100%
Simulated radiographAttenuation DRR
Loading CT volume…
Image controls

Display controls update the radiograph immediately.

Current anatomy track

Read the projection, then reconstruct the anatomy

Module guidance will appear after the anatomy package loads.

Evidence & governance Assumptions · limitations · evidence · provenance
Evidence & governance

How to interpret this lab

Model assumptions
  • The DRR integrates a simplified monochromatic attenuation estimate derived from Hounsfield units along parallel rays.
  • The 3D surfaces are generated from physician-reviewed label volumes; the radiograph is generated from the aligned computed tomography (CT) volume.
  • Hidden labelled structures are replaced with an approximate 40 HU soft-tissue attenuation rather than air.
  • Hip positioning applies rigid femoral motion with a blended, approximate soft-tissue deformation around the reviewed femoral-head centre.
Limitations
  • The renderer does not model a clinical X-ray spectrum, scatter, beam hardening, detector response, image noise, or patient-specific exposure.
  • Joint motion is an educational approximation without collision detection, dislocation constraints, muscle forces, or validated biomechanics.
  • The current scan represents one individual anatomy and does not demonstrate normal population variation or every pathological pattern.
  • Projected landmark and measurement guides are reviewed teaching annotations, not validated clinical measurements. Linear values use CT-space millimetres in this parallel-ray model and do not reproduce clinical radiographic magnification.
Evidence and references 11 selected sources

Projection selection and hip-evaluation teaching are informed by the following sources. View-specific content remains under active review while this module is in Preview.

  1. American College of Radiology, Society for Pediatric Radiology, and Society of Skeletal Radiology. Practice parameter for radiography of the extremities.
  2. Clohisy JC, Carlisle JC, Beaulé PE, et al. A systematic approach to the plain radiographic evaluation of the young adult hip. J Bone Joint Surg Am. 2008;90 Suppl 4:47–66. PubMed.
  3. Lim SJ, Park YS. Plain Radiography of the Hip: A Review of Radiographic Techniques and Image Features. Hip Pelvis. 2015;27(3):125–134. Full text.
  4. Yeap PM, Budak MJ. The pelvic radiograph: lines, arcs and stripes. Singapore Med J. 2021;62(7):333–340. Full text.
  5. American College of Radiology, American Society of Spine Radiology, Society for Pediatric Radiology, and Society of Skeletal Radiology. Practice parameter for spine radiography.
  6. Tazeabadi SA, Noroozi SG, Salehzadeh M, et al. Evaluation of Judet view radiographs accuracy in classification of acetabular fractures compared with three-dimensional computerized tomographic scan: a retrospective study. BMC Musculoskelet Disord. 2020;21:405. PubMed.
  7. Karkhur Y, Tiwari A, Maini L, Bansal V, Kakralia A. Radiological evaluation of pelvic inlet and outlet radiographic view in Indian population. J Clin Orthop Trauma. 2018;9(4):334–337. PubMed.
  8. Vrtovec T, Pernuš F, Likar B. A review of methods for quantitative evaluation of spinal curvature. Eur Spine J. 2009;18(5):593–607. Full text.
  9. Koslosky E, Gendelberg D. Classification in Brief: The Meyerding Classification System of Spondylolisthesis. Clin Orthop Relat Res. 2020;478(5):1125–1130. Full text.
  10. Chen X, Deng Q, Wang Q, et al. Image quality control in lumbar spine radiography using enhanced U-Net neural networks. Front Public Health. 2022;10:891766. Full text.
  11. Siddon RL. Fast calculation of the exact radiological path for a three-dimensional CT array. Med Phys. 1985;12(2):252–255. PubMed.
Attribution and provenance

The displayed CT volume, reviewed labels, generated meshes, processing history, source citation, and licence are defined by the selected dataset manifest. Dataset-specific attribution appears in the footer below.

Mesh and volume assets were prepared with OrthoAnimate Dataset Builder. The browser renderer uses a locally built subset of vtk.js; see Third-party notices.

Report an errorEditorial and corrections policy