Higher Order Total Variation Super-Resolution from a Single Trabecular Bone Image

Alina Toma (1) , Bruno Sixou (1) , Loïc Denis (2) , J.-B. Pialat (3) , Françoise Peyrin (4, 5)

1 Imagerie Tomographique et Radiothérapie
2 LHC - Laboratoire Hubert Curien [Saint Etienne]
3 LYOS - Physiopathologie, diagnostic et traitements des maladies osseuses / Pathophysiology, Diagnosis & Treatments of Bone Diseases
4 ESRF - European Synchrotron Radiation Facility
5 CREATIS - Centre de Recherche en Acquisition et Traitement de l'Image pour la Santé

Osteoporosis is characterized by a low bone mass density and deterioration of bone micro-architecture. Despite the considerable progress in Computed Tomography (CT), the investigation of 3D trabecular bone micro-architecture in-vivo remains limited due to a lack of spatial resolution compared to the trabeculae size. To improve the analysis of trabecular bone from in-vivo CT images, we investigate super-resolution methods to estimate a higher spatial resolution image from a single lower spatial resolution image. To solve this inverse problem, we considered two regularization strategies involving first or second order differential operators. The methods are tested on experimental micro-CT trabecular bone images at 20 µm which are used as reference images. The first tests suggest that both methods give similar results but total variation regularization implemented with the alternating direction method of multipliers algorithm is more efficient to recover correctly some structural parameters.

Domains: Engineering Sciences [physics]; Signal and Image processing; Computer Science [cs]; Signal and Image Processing

Alina Toma, Bruno Sixou, Loïc Denis, J.-B. Pialat, Françoise Peyrin. Higher Order Total Variation Super-Resolution from a Single Trabecular Bone Image. International Symposium on Biomedical Imaging, May 2014, Beijing, China. pp.FrA01.7. ⟨ujm-01018098⟩