Accurate compensation for intra-operative brain shift remains a fundamental challenge in neurosurgical procedures, as misalignment between pre-operative and intra-operative images can lead to suboptimal surgical guidance. In this work, we propose a bidirectional, unsupervised 3D brain shift compensation framework for n...
Eashrat Jahan Muniya, G. Kronreif, A. Biguri et al.· Journal of neuroradiology =...· 0 citations
Sparse-view computed tomography (CT) reduces radiation dose and acquisition time and may mitigate motion artifacts. However, angular undersampling provides insufficient information to determine the image uniquely and stably. Limited-angle CT, arising from restricted angular coverage, produces strongly directional infor...
Honglei Brinkmann, C. Schönlieb, A. Biguri· 0 citations
Plug-and-Play (PnP) algorithms are a class of iterative methods for inverse imaging. Within an optimization algorithm, they combine a flexible fidelity term, encoding the forward operator, and a pretrained image denoiser, in order to deal with more severe corruptions such as blurring or downsampling when reconstructing...
Zi-Qi Qin, Hong-Wei Tan, A. Biguri et al.· 0 citations
Adaptive regularization is an effective means of improving the flexibility of classical variational reconstruction methods while retaining their interpretability and mathematical structure. In this work, we propose an approach for learning deep-reparameterized adaptive regularization maps (DREAM) for Total Variation (T...
T. Vu, A. Biguri, Christoph Kolbitsch et al.· 0 citations
A unified framework that decomposes splitting-based reconstruction into these three components is introduced, enabling controlled comparison of existing methods and two incremental extensions: multi-partition splitting and an alternative inference strategy.
Nadja Gruber, Lukas Neumann, A. Biguri et al.· arXiv.org· 0 citations
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