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Found 3 papers, 1 papers with code
GroupMixer: Patch-based Group Convolutional Neural Network for Breast Cancer Detection from Histopathological Images
In this paper, we borrowed the previously introduced idea of integrating a fully Convolutional Neural Network architecture with Patch Embedding operation and presented an efficient CNN architecture for breast cancer malignancy detection from histopathological images.
Isotropic multichannel total variation framework for joint reconstruction of multicontrast parallel MRI
Purpose: To develop a synergistic image reconstruction framework that exploits multicontrast (MC), multicoil, and compressed sensing (CS) redundancies in magnetic resonance imaging (MRI).
Compressed MRI Reconstruction Exploiting a Rotation-Invariant Total Variation Discretization
Inspired by the first-order method of Malitsky and Pock, we propose a new variational framework for compressed MR image reconstruction which introduces the application of a rotation-invariant discretization of total variation functional into MR imaging while exploiting BM3D frame as a sparsifying transform.
