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Registration of Free-Breathing 3D+t Abdominal Perfusion CT Images via Co-segmentation

  • Raphael Prevost
  • Blandine Romain
  • Remi Cuingnet
  • Benoit Mory
  • Laurence Rouet
  • Olivier Lucidarme
  • Laurent D. Cohen
  • Roberto Ardon
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8150)

Abstract

Dynamic contrast-enhanced computed tomography (DCE-CT) is a valuable imaging modality to assess tissues properties, particularly in tumours, by estimating pharmacokinetic parameters from the evolution of pixels intensities in 3D+t acquisitions. However, this requires a registration of the whole sequence of volumes, which is challenging especially when the patient breathes freely. In this paper, we propose a generic, fast and automatic method to address this problem. As standard iconic registration methods are not robust to contrast intake, we rather rely on the segmentation of the organ of interest. This segmentation is performed jointly with the registration of the sequence within a novel co-segmentation framework. Our approach is based on implicit template deformation, that we extend to a co-segmentation algorithm which provides as outputs both a segmentation of the organ of interest in every image and stabilising transformations for the whole sequence. The proposed method is validated on 15 datasets acquired from patients with renal lesions and shows improvement in terms of registration and estimation of pharmacokinetic parameters over the state-of-the-art method.

Keywords

Active Contour Rigid Transformation Contrast Agent Injection Robust Registration Kidney Segmentation 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Raphael Prevost
    • 1
    • 2
  • Blandine Romain
    • 1
    • 3
  • Remi Cuingnet
    • 1
  • Benoit Mory
    • 1
  • Laurence Rouet
    • 1
  • Olivier Lucidarme
    • 4
  • Laurent D. Cohen
    • 2
  • Roberto Ardon
    • 1
  1. 1.Philips Research MedisysSuresnesFrance
  2. 2.CEREMADE UMR 7534, CNRSUniversité Paris DauphineParisFrance
  3. 3.MAS, Ecole Centrale ParisChatenay MalabryFrance
  4. 4.Hôpital La Pitié-Salpétrière, AP-HPParisFrance

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