{"slug": "cad-to-ct-registration-of-cylindrical-objects-via-ellipse-based-axis-estimation", "title": "CAD-to-CT Registration of Cylindrical Objects via Ellipse-Based Axis Estimation", "summary": "Researchers have developed a two-stage geometric registration method that aligns CAD models to CT scans of cylindrical objects by detecting elliptical cross-sections and estimating the 3D rotation axis. The approach achieves tilt and orientation errors below 0.1 degrees without requiring intensity calibration or feature matching, overcoming limitations of traditional intensity-based and point-based algorithms. This method provides ground truth geometry for machine learning applications and automated analysis in industrial CT workflows.", "body_md": "arXiv:2606.02935v1 Announce Type: new\nAbstract: Accurate registration of CAD models to CT scans is essential for establishing ground truth geometry in volumetric imaging. Obtaining reliable object masks is of growing importance in machine learning settings; as recent architectures grow more capable, huge datasets are required to fully utilise their capabilities. Traditional intensity-based methods fail when CT grayscale values lack calibration references, while point-based algorithms (e.g., ICP, RANSAC) require feature correspondence unavailable between idealized CAD geometry and noisy volumetric CT data.\nWe propose a two-stage geometric registration method for cylindrical objects (ionization chambers) that takes advantage of the distinctive geometric features of the objects. First, we estimate the 3D rotation axis by detecting elliptical cross-sections across CT slices, fitting ellipses to edge-detected contours, and performing PCA on the fitted ellipse centers after RANSAC outlier removal. Second, we voxelize the CAD model, orient it along the detected axis, and maximize volumetric overlap with the CT scan through translational adjustment.\nThis approach achieves robust registration with tilt and orientation errors below $0.1^\\circ$ without intensity calibration or feature matching. Once registered, the aligned CAD model provides ground truth geometry for applications including machine learning-based object localization and automated analysis in industrial CT workflows.", "url": "https://wpnews.pro/news/cad-to-ct-registration-of-cylindrical-objects-via-ellipse-based-axis-estimation", "canonical_source": "https://arxiv.org/abs/2606.02935", "published_at": "2026-06-03 04:00:00+00:00", "updated_at": "2026-06-03 04:19:55.581768+00:00", "lang": "en", "topics": ["computer-vision", "machine-learning", "ai-research"], "entities": [], "alternates": {"html": "https://wpnews.pro/news/cad-to-ct-registration-of-cylindrical-objects-via-ellipse-based-axis-estimation", "markdown": "https://wpnews.pro/news/cad-to-ct-registration-of-cylindrical-objects-via-ellipse-based-axis-estimation.md", "text": "https://wpnews.pro/news/cad-to-ct-registration-of-cylindrical-objects-via-ellipse-based-axis-estimation.txt", "jsonld": "https://wpnews.pro/news/cad-to-ct-registration-of-cylindrical-objects-via-ellipse-based-axis-estimation.jsonld"}}