X-Ray In-Depth Decomposition: Revealing the Latent Structures

  • Shadi AlbarqouniEmail author
  • Javad Fotouhi
  • Nassir Navab
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 10435)


X-ray is the most readily available imaging modality and has a broad range of applications that spans from diagnosis to intra-operative guidance in cardiac, orthopedics, and trauma procedures. Proper interpretation of the hidden and obscured anatomy in X-ray images remains a challenge and often requires high radiation dose and imaging from several perspectives. In this work, we aim at decomposing the conventional X-ray image into d X-ray components of independent, non-overlapped, clipped sub-volume, that separate rigid structures into distinct layers, leaving all deformable organs in one layer, such that the sum resembles the original input. Our proposed model is validaed on 6 clinical datasets (\(\sim \)7200 X-ray images) in addition to 615 real chest X-ray images. Despite the challenging aspects of modeling such a highly ill-posed problem, exciting and encouraging results are obtained paving the path for further contributions in this direction.


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Copyright information

© Springer International Publishing AG 2017

Authors and Affiliations

  • Shadi Albarqouni
    • 1
    Email author
  • Javad Fotouhi
    • 2
  • Nassir Navab
    • 1
    • 2
  1. 1.Computer Aided Medical Procedures (CAMP)Technische Universität MünchenMunichGermany
  2. 2.Whiting School of EngineeringJohns Hopkins UniversityBaltimoreUSA

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