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Found 4 papers, 2 papers with code
NeuralOCT: Airway OCT Analysis via Neural Fields
Our interest in this work is OCT in the context of airway abnormalities in infants and children where the high resolution of OCT and the fact that it is radiation-free is important.
NAISR: A 3D Neural Additive Model for Interpretable Shape Representation
However, given a set of 3D shapes with associated covariates there is at present no shape representation method which allows to precisely represent the shapes while capturing the individual dependencies on each covariate.
iSegFormer: Interactive Segmentation via Transformers with Application to 3D Knee MR Images
We propose iSegFormer, a memory-efficient transformer that combines a Swin transformer with a lightweight multilayer perceptron (MLP) decoder.
Reducing Magnetic Resonance Image Spacing by Learning Without Ground-Truth
In this work, we propose a novel deep-learning-based super-resolution algorithm to generate high-resolution (HR) MR images with small slice spacing from low-resolution (LR) inputs of large slice spacing.
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