Nonlinear diffusion constraints for reconstructing subsampled rotational angiography data

Hélène Langet; Aymeric Reshef; Cyril Riddell; Yves Trousset; Arthur Tenenhaus; Elisabeth Lahalle; Gilles Fleury; Nikos Paragios

Conference papers

Nonlinear diffusion constraints for reconstructing subsampled rotational angiography data

Hélène Langet ^{1, 2} Aymeric Reshef ^{2, 3} Cyril Riddell ⁴ Yves Trousset ⁴ Arthur Tenenhaus ⁵ Elisabeth Lahalle ⁵ Gilles Fleury ⁵ Nikos Paragios ^{6, 7, 8, 9, 10, 11}

1 Medisys - MedisysResearch Lab

2 GET - GET

3 ENS Paris - École normale supérieure - Paris

4 GE Healthcare - General Electric Medical Systems [Buc]

5 E3S - Supélec Sciences des Systèmes

6 GALEN - Organ Modeling through Extraction, Representation and Understanding of Medical Image Content

Ecole Centrale Paris, Inria Saclay - Ile de France

7 MAS - Mathématiques Appliquées aux Systèmes - EA 4037

8 imagine [Marne-la-Vallée]

LIGM - Laboratoire d'Informatique Gaspard-Monge, CSTB - Centre Scientifique et Technique du Bâtiment, ENPC - École des Ponts ParisTech

9 LIGM - Laboratoire d'Informatique Gaspard-Monge

10 UPEM - Université Paris-Est Marne-la-Vallée

11 ENPC - École des Ponts ParisTech

Abstract : Interventional imaging with cone-beam C-arm CT often lacks sufficient sampling. Compressed sensing based reconstruction algorithms have shown promising results to improve image quality in this context using sparsity constraints. Compressed sensing theory by itself assumes random measurements and l1 penalties. In practice, benefits are seen with uniform subsampling patterns. Here, we investigate substituting l1 total variation with a nonlinear diffusion constraint and show on a clinical data set that image quality is also improved. This result adds flexibility to the design of CS-based algorithms as C-arm CT images may not be so well approximated by piecewise constant functions.

Document type :

Conference papers

Domain :

Computer Science [cs] / Medical Imaging

Computer Science [cs] / Signal and Image Processing

Engineering Sciences [physics] / Signal and Image processing

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https://hal-supelec.archives-ouvertes.fr/hal-00933983
Contributor : Alexandra Siebert <>
Submitted on : Tuesday, January 21, 2014 - 2:11:41 PM
Last modification on : Tuesday, July 20, 2021 - 3:03:56 AM

Nonlinear diffusion constraints for reconstructing subsampled rotational angiography data

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Nonlinear diffusion constraints for reconstructing subsampled rotational angiography data

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