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Biomedical Image Reconstruction: A Survey

arXiv 2301.11813 ↗First posted 4 Jan 2023eess.IV cs.CVcited by 0

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Abstract (arXiv)

Biomedical image reconstruction research has been developed for more than five decades, giving rise to various techniques such as central and filtered back projection. With the rise of deep learning technology, biomedical image reconstruction field has undergone a massive paradigm shift from analytical and iterative methods to deep learning methods To drive scientific discussion on advanced deep learning techniques for biomedical image reconstruction, a workshop focusing on deep biomedical image reconstruction, MLMIR, is introduced and is being held yearly since 2018. This survey paper is aimed to provide basic knowledge in biomedical image reconstruction and the current research trend in biomedical image reconstruction based on the publications in MLMIR. This survey paper is intended for machine learning researchers to grasp a general understanding of the biomedical image reconstruction field and the current research trend in deep biomedical image reconstruction.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 26 of its 84 references that are in the map. First posted on arXiv 4 Jan 2023.

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References · 26

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14 more
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