1 citations · 2 across the 3 of their papers we have counts for
5 papers
A Field of Experts Prior for Adapting Neural Networks at Test Time
Neerav Karani, Georg Brunner, Ertunc Erdil +4
Performance of convolutional neural networks (CNNs) in image analysis tasks is often marred in the presence of acquisition-related distribution shifts between training and test ima…
Joint reconstruction and bias field correction for undersampled MR imaging
Mélanie Gaillochet, Kerem C. Tezcan, Ender Konukoglu
Undersampling the k-space in MRI allows saving precious acquisition time, yet results in an ill-posed inversion problem. Recently, many deep learning techniques have been developed…
Modelling the Distribution of 3D Brain MRI using a 2D Slice VAE
Anna Volokitin, Ertunc Erdil, Neerav Karani +4
Probabilistic modelling has been an essential tool in medical image analysis, especially for analyzing brain Magnetic Resonance Images (MRI). Recent deep learning techniques for es…
Unsupervised Lesion Detection via Image Restoration with a Normative Prior
Xiaoran Chen, Suhang You, Kerem Can Tezcan +1
Unsupervised lesion detection is a challenging problem that requires accurately estimating normative distributions of healthy anatomy and detecting lesions as outliers without trai…
PHiSeg: Capturing Uncertainty in Medical Image Segmentation
Christian F. Baumgartner, Kerem C. Tezcan, Krishna Chaitanya +6
Segmentation of anatomical structures and pathologies is inherently ambiguous. For instance, structure borders may not be clearly visible or different experts may have different st…