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Found 7 papers, 6 papers with code
Multi-task Learning for Optical Coherence Tomography Angiography (OCTA) Vessel Segmentation
In this paper, we propose a novel multi-task learning method for OCTA segmentation, called OCTA-MTL, that leverages an image-to-DT (Distance Transform) branch and an adaptive loss combination strategy.
Learning Fourier-Constrained Diffusion Bridges for MRI Reconstruction
Instead of the target transformation from undersampled to fully-sampled data required for MRI reconstruction, common diffusion priors are trained to learn a task-agnostic transformation from an asymptotic start-point of Gaussian noise onto the finite end-point of fully-sampled data.
COVID-19 Detection from Respiratory Sounds with Hierarchical Spectrogram Transformers
Monitoring of prevalent airborne diseases such as COVID-19 characteristically involves respiratory assessments.
Unsupervised Medical Image Translation with Adversarial Diffusion Models
Extensive assessments are reported on the utility of SynDiff against competing GAN and diffusion models in multi-contrast MRI and MRI-CT translation.
Ranked #7 on
Image-to-Image Translation
on IXI
One Model to Unite Them All: Personalized Federated Learning of Multi-Contrast MRI Synthesis
As such, pFLSynth enables training of a unified synthesis model that can reliably generalize across multiple sites and translation tasks.
BolT: Fused Window Transformers for fMRI Time Series Analysis
Encoding is performed on temporally-overlapped windows within the time series to capture local representations.
ResViT: Residual vision transformers for multi-modal medical image synthesis
Here, we propose a novel generative adversarial approach for medical image synthesis, ResViT, that leverages the contextual sensitivity of vision transformers along with the precision of convolution operators and realism of adversarial learning.}
Ranked #1 on
Image-to-Image Translation
on IXI
