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Found 6 papers, 0 papers with code
A Learning-from-noise Dilated Wide Activation Network for denoising Arterial Spin Labeling (ASL) Perfusion Images
The results showed that the learning-from-noise strategy produced better output quality than ASLDN trained with relatively high SNR reference.
OCT segmentation: Integrating open parametric contour model of the retinal layers and shape constraint to the Mumford-Shah functional
The retinal layer boundary model consists of 9 open parametric contours representing the 9 retinal layers in OCT images.
Denoising Arterial Spin Labeling Cerebral Blood Flow Images Using Deep Learning
Arterial spin labeling perfusion MRI is a noninvasive technique for measuring quantitative cerebral blood flow (CBF), but the measurement is subject to a low signal-to-noise-ratio(SNR).
Tensor Based Second Order Variational Model for Image Reconstruction
Second order total variation (SOTV) models have advantages for image reconstruction over their first order counterparts including their ability to remove the staircase artefact in the reconstructed image, but they tend to blur the reconstructed image.
Automated Segmentation of Retinal Layers from Optical Coherent Tomography Images Using Geodesic Distance
OCT image segmentation to localise retinal layer boundaries is a fundamental procedure for diagnosing and monitoring the progression of retinal and optical nerve disorders.
Parallel AdaBoost Algorithm for Gabor Wavelet Selection in Face Recognition
In this paper, the problem of automatic Gabor wavelet selection for face recognition is tackled by introducing an automatic algorithm based on Parallel AdaBoosting method.
