207 citations · 349 across the 6 of their papers we have counts for
11 papers · 1 filter
Importance Driven Continual Learning for Segmentation Across Domains
Sinan Özgür Özgün, Anne-Marie Rickmann, Abhijit Guha Roy +1
The ability of neural networks to continuously learn and adapt to new tasks while retaining prior knowledge is crucial for many applications. However, current neural networks tend…
'Squeeze & Excite' Guided Few-Shot Segmentation of Volumetric Images
Abhijit Guha Roy, Shayan Siddiqui, Sebastian Pölsterl +2
Deep neural networks enable highly accurate image segmentation, but require large amounts of manually annotated data for supervised training. Few-shot learning aims to address this…
Bayesian QuickNAT: Model Uncertainty in Deep Whole-Brain Segmentation for Structure-wise Quality Control
Abhijit Guha Roy, Sailesh Conjeti, Nassir Navab +1
We introduce Bayesian QuickNAT for the automated quality control of whole-brain segmentation on MRI T1 scans. Next to the Bayesian fully convolutional neural network, we also prese…
InfiNet: Fully Convolutional Networks for Infant Brain MRI Segmentation
Shubham Kumar, Sailesh Conjeti, Abhijit Guha Roy +2
We present a novel, parameter-efficient and practical fully convolutional neural network architecture, termed InfiNet, aimed at voxel-wise semantic segmentation of infant brain MRI…
Learning Optimal Deep Projection of F-FDG PET Imaging for Early Differential Diagnosis of Parkinsonian Syndromes
Shubham Kumar, Abhijit Guha Roy, Ping Wu +10
Several diseases of parkinsonian syndromes present similar symptoms at early stage and no objective widely used diagnostic methods have been approved until now. Positron emission t…
Recalibrating Fully Convolutional Networks with Spatial and Channel 'Squeeze & Excitation' Blocks
Abhijit Guha Roy, Nassir Navab, Christian Wachinger
In a wide range of semantic segmentation tasks, fully convolutional neural networks (F-CNNs) have been successfully leveraged to achieve state-of-the-art performance. Architectural…