3D Digital Breast Tomosynthesis Using Total Variation Regularization

Authors:
Iason Kastanis;Simon Arridge;Alex Stewart;Spencer Gunn;Christer Ullberg;Tom Francke
Affiliations:
Dexela Ltd, London, UK NW1 8NZ;Department of Computer Science, UCL, London, UK WC1E 6BT;Dexela Ltd, London, UK NW1 8NZ;Dexela Ltd, London, UK NW1 8NZ;XCounter AB, Danderyd, Sweden SE-182 33;XCounter AB, Danderyd, Sweden SE-182 33
Venue:
IWDM '08 Proceedings of the 9th international workshop on Digital Mammography
Year:
2008

Citing 6
Cited 2

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Abstract

3D digital breast imaging promises to significantly reduce both false negatives and false positives, allowing the earlier detection of cancer while reducing the occurrence of callbacks. In this paper we have developed an iterative algorithm that improves on the quality of the reconstructed images over current algorithms like filtered back projection. Our algorithm uses Total Variation to restrain the noise while enhancing edge features. We have applied this algorithm to data obtained using the XCounter mammography system.