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Document type:
Konferenzbeitrag 
Author(s):
Albarqouni, S.; Fotouhi, J.; Navab, N. 
Title:
X-ray In-Depth Decomposition: Revealing The Latent Structures 
Abstract:
X-ray radiography 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, cl...    »
 
Keywords:
miccai,Xray,Depth,deeplearning 
Book / Congress title:
International Conference on Medical Image Computing and Computer-Assisted Intervention 
Organization:
Springer 
Year:
2017 
Pages:
444--452