Structure-Guided MR-to-CT Synthesis with Spatial and Semantic Alignments for Attenuation Correction of Whole-Body PET/MR Imaging Article Swipe
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· 2024
· Open Access
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· DOI: https://doi.org/10.48550/arxiv.2411.17488
Deep-learning-based MR-to-CT synthesis can estimate the electron density of tissues, thereby facilitating PET attenuation correction in whole-body PET/MR imaging. However, whole-body MR-to-CT synthesis faces several challenges including the issue of spatial misalignment and the complexity of intensity mapping, primarily due to the variety of tissues and organs throughout the whole body. Here we propose a novel whole-body MR-to-CT synthesis framework, which consists of three novel modules to tackle these challenges: (1) Structure-Guided Synthesis module leverages structure-guided attention gates to enhance synthetic image quality by diminishing unnecessary contours of soft tissues; (2) Spatial Alignment module yields precise registration between paired MR and CT images by taking into account the impacts of tissue volumes and respiratory movements, thus providing well-aligned ground-truth CT images during training; (3) Semantic Alignment module utilizes contrastive learning to constrain organ-related semantic information, thereby ensuring the semantic authenticity of synthetic CT images.We conduct extensive experiments to demonstrate that the proposed whole-body MR-to-CT framework can produce visually plausible and semantically realistic CT images, and validate its utility in PET attenuation correction.
Related Topics
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2411.17488
- https://arxiv.org/pdf/2411.17488
- OA Status
- green
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4404988907
Raw OpenAlex JSON
- OpenAlex ID
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https://openalex.org/W4404988907Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.48550/arxiv.2411.17488Digital Object Identifier
- Title
-
Structure-Guided MR-to-CT Synthesis with Spatial and Semantic Alignments for Attenuation Correction of Whole-Body PET/MR ImagingWork title
- Type
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preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2024Year of publication
- Publication date
-
2024-11-26Full publication date if available
- Authors
-
Jiaxu Zheng, Zhenrong Shen, Lichi Zhang, Qun ChenList of authors in order
- Landing page
-
https://arxiv.org/abs/2411.17488Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2411.17488Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2411.17488Direct OA link when available
- Concepts
-
Correction for attenuation, Attenuation, Nuclear medicine, Artificial intelligence, Computer science, Computer vision, Medicine, Physics, Positron emission tomography, OpticsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
0Total citation count in OpenAlex
- Related works (count)
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10Other works algorithmically related by OpenAlex
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