PLOSL: Population learning followed by one shot learning pulmonary image registration using tissue volume preserving and vesselness constraints

This paper presents the Population Learning followed by One Shot Learning (PLOSL) pulmonary image registration method. PLOSL is a fast unsupervised learning-based framework for 3D-CT pulmonary image registration algorithm based on combining population learning (PL) and one-shot learning (OSL). The P...

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Bibliographic Details
Main Authors:	Christensen, G.E (Author), Durumeric, O.C (Author), Hoffman, E.A (Author), Pan, Y. (Author), Reinhardt, J.M (Author), Schroeder, J.D (Author), Wang, D. (Author)
Format:	Article
Language:	English
Published:	Elsevier B.V. 2022
Subjects:	article Computed tomography images computer assisted tomography Computerized tomography Convolution Convolutional encoder-decoder network Convolutional encoders convolutional neural network Decoding deep learning Deep learning Encoder-decoder four dimensional computed tomography human tissue Image registration image registration algorithm Images registration learning lung blood vessel Network coding One-shot learning Pulmonary images Tissue Transfer learning transfer of learning Volume-preserving
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PLOSL: Population learning followed by one shot learning pulmonary image registration using tissue volume preserving and vesselness constraints

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