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Found 6 papers, 0 papers with code
DuDoUniNeXt: Dual-domain unified hybrid model for single and multi-contrast undersampled MRI reconstruction
Multi-contrast (MC) Magnetic Resonance Imaging (MRI) reconstruction aims to incorporate a reference image of auxiliary modality to guide the reconstruction process of the target modality.
O-PRESS: Boosting OCT axial resolution with Prior guidance, Recurrence, and Equivariant Self-Supervision
Optical coherence tomography (OCT) is a noninvasive technology that enables real-time imaging of tissue microanatomies.
Unified Multi-Modal Image Synthesis for Missing Modality Imputation
Besides, we propose a Dynamic Feature Unification Module to integrate information from a varying number of available modalities, which enables the network to be robust to random missing modalities.
On the impact of incorporating task-information in learning-based image denoising
The task-component was designed to measure the performance of a numerical observer (NO) on a signal detection task.
A Hybrid Approach for Approximating the Ideal Observer for Joint Signal Detection and Estimation Tasks by Use of Supervised Learning and Markov-Chain Monte Carlo Methods
Specifically, a hybrid approach is developed that combines a multi-task convolutional neural network and a Markov-Chain Monte Carlo (MCMC) method in order to approximate the IO for detection-estimation tasks.
Assessing the Impact of Deep Neural Network-based Image Denoising on Binary Signal Detection Tasks
The performance of the ideal observer (IO) and common linear numerical observers are quantified and detection efficiencies are computed to assess the impact of the denoising operation on task performance.
