13 citations · 33 across the 9 of their papers we have counts for
10 papers
Cortical analysis of heterogeneous clinical brain MRI scans for large-scale neuroimaging studies
Karthik Gopinath, Douglas N. Greve, Sudeshna Das +3
Surface analysis of the cortex is ubiquitous in human neuroimaging with MRI, e.g., for cortical registration, parcellation, or thickness estimation. The convoluted cortical geometr…
Graph Domain Adaptation for Alignment-Invariant Brain Surface Segmentation
Karthik Gopinath, Christian Desrosiers, Herve Lombaert
The varying cortical geometry of the brain creates numerous challenges for its analysis. Recent developments have enabled learning surface data directly across multiple brain surfa…
Learnable Pooling in Graph Convolution Networks for Brain Surface Analysis
Karthik Gopinath, Christian Desrosiers, Herve Lombaert
Brain surface analysis is essential to neuroscience, however, the complex geometry of the brain cortex hinders computational methods for this task. The difficulty arises from a dis…
Spectral Graph Transformer Networks for Brain Surface Parcellation
Ran He, Karthik Gopinath, Christian Desrosiers +1
The analysis of the brain surface modeled as a graph mesh is a challenging task. Conventional deep learning approaches often rely on data lying in the Euclidean space. As an extens…
A deep learning framework for segmentation of retinal layers from OCT images
Karthik Gopinath, Samrudhdhi B Rangrej, Jayanthi Sivaswamy
Segmentation of retinal layers from Optical Coherence Tomography (OCT) volumes is a fundamental problem for any computer aided diagnostic algorithm development. This requires prepr…
HyperDense-Net: A hyper-densely connected CNN for multi-modal image segmentation
Jose Dolz, Karthik Gopinath, Jing Yuan +3
Recently, dense connections have attracted substantial attention in computer vision because they facilitate gradient flow and implicit deep supervision during training. Particularl…
Graph Convolutions on Spectral Embeddings: Learning of Cortical Surface Data
Karthik Gopinath, Christian Desrosiers, Herve Lombaert
Neuronal cell bodies mostly reside in the cerebral cortex. The study of this thin and highly convoluted surface is essential for understanding how the brain works. The analysis of…
A Generalized Motion Pattern and FCN based approach for retinal fluid detection and segmentation
Shivin Yadav, Karthik Gopinath, Jayanthi Sivaswamy
SD-OCT is a non-invasive cross-sectional imaging modality used for diagnosis of macular defects. Efficient detection and segmentation of the abnormalities seen as biomarkers in OCT…
Segmentation of retinal cysts from Optical Coherence Tomography volumes via selective enhancement
Karthik Gopinath, Jayanthi Sivaswamy
Automated and accurate segmentation of cystoid structures in Optical Coherence Tomography (OCT) is of interest in the early detection of retinal diseases. It is, however, a challen…
Domain knowledge assisted cyst segmentation in OCT retinal images
Karthik Gopinath, Jayanthi Sivaswamy
3D imaging modalities are becoming increasingly popular and relevant in retinal imaging owing to their effectiveness in highlighting structures in sub-retinal layers. OCT is one su…