4 citations · 16 across the 5 of their papers we have counts for
6 papers
Compressive lensless endoscopy with partial speckle scanning
Stéphanie Guérit, Siddharth Sivankutty, John Aldo Lee +2
The lensless endoscope (LE) is a promising device to acquire in vivo images at a cellular scale. The tiny size of the probe enables a deep exploration of the tissues. Lensless endo…
Knowing what you know in brain segmentation using Bayesian deep neural networks
Patrick McClure, Nao Rho, John A. Lee +7
In this paper, we describe a Bayesian deep neural network (DNN) for predicting FreeSurfer segmentations of structural MRI volumes, in minutes rather than hours. The network was tra…
Compressive Sampling Approach for Image Acquisition with Lensless Endoscope
Stéphanie Guérit, Siddharth Sivankutty, Camille Scotté +3
The lensless endoscope is a promising device designed to image tissues in vivo at the cellular scale. The traditional acquisition setup consists in raster scanning during which the…
Capturing Variabilities from Computed Tomography Images with Generative Adversarial Networks
Umair Javaid, John A. Lee
With the advent of Deep Learning (DL) techniques, especially Generative Adversarial Networks (GANs), data augmentation and generation are quickly evolving domains that have raised…
Blind Deconvolution of PET Images using Anatomical Priors
Stéphanie Guérit, Adriana González, Anne Bol +2
Images from positron emission tomography (PET) provide metabolic information about the human body. They present, however, a spatial resolution that is limited by physical and instr…
Post-Reconstruction Deconvolution of PET Images by Total Generalized Variation Regularization
Stéphanie Guérit, Laurent Jacques, Benoît Macq +1
Improving the quality of positron emission tomography (PET) images, affected by low resolution and high level of noise, is a challenging task in nuclear medicine and radiotherapy.…