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Found 10 papers, 1 papers with code
Cortical analysis of heterogeneous clinical brain MRI scans for large-scale neuroimaging studies
Here we present the first method for cortical reconstruction, registration, parcellation, and thickness estimation for clinical brain MRI scans of any resolution and pulse sequence.
Graph Domain Adaptation for Alignment-Invariant Brain Surface Segmentation
The varying cortical geometry of the brain creates numerous challenges for its analysis.
Learnable Pooling in Graph Convolution Networks for Brain Surface Analysis
This paper proposes a new learnable graph pooling method for processing multiple surface-valued data to output subject-based information.
Spectral Graph Transformer Networks for Brain Surface Parcellation
Our alignment and graph processing method provides a fast analysis of brain surfaces.
A deep learning framework for segmentation of retinal layers from OCT images
Segmentation of retinal layers from Optical Coherence Tomography (OCT) volumes is a fundamental problem for any computer aided diagnostic algorithm development.
HyperDense-Net: A hyper-densely connected CNN for multi-modal image segmentation
Therefore, the proposed network has total freedom to learn more complex combinations between the modalities, within and in-between all the levels of abstraction, which increases significantly the learning representation.
Ranked #1 on
Medical Image Segmentation
on iSEG 2017 Challenge
Graph Convolutions on Spectral Embeddings: Learning of Cortical Surface Data
This paper presents a novel approach for learning and exploiting surface data directly across surface domains.
A Generalized Motion Pattern and FCN based approach for retinal fluid detection and segmentation
SD-OCT is a non-invasive cross-sectional imaging modality used for diagnosis of macular defects.
Segmentation of retinal cysts from Optical Coherence Tomography volumes via selective enhancement
The robustness of the algorithm was examined by cross-validation on the DME and AEI (private) datasets and a mean DC values obtained were 0. 69 and 0. 79, respectively.
Domain knowledge assisted cyst segmentation in OCT retinal images
OCT is one such modality which has great importance in the context of analysis of cystoid structures in subretinal layers.
