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Found 4 papers, 1 papers with code
Sparse2Inverse: Self-supervised inversion of sparse-view CT data
Sparse-view computed tomography (CT) enables fast and low-dose CT imaging, an essential feature for patient-save medical imaging and rapid non-destructive testing.
Variational multichannel multiclass segmentation using unsupervised lifting with CNNs
We propose an unsupervised image segmentation approach, that combines a variational energy functional and deep convolutional neural networks.
Lifting-based variational multiclass segmentation algorithm: design, convergence analysis, and implementation with applications in medical imaging
We propose, analyze and realize a variational multiclass segmentation scheme that partitions a given image into multiple regions exhibiting specific properties.
Projection-Based 2.5D U-net Architecture for Fast Volumetric Segmentation
While for 2D images these networks are also computationally efficient, 3D convolutions have huge storage requirements and require long training time.
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