Skull Stripping
12 papers with code • 0 benchmarks • 0 datasets
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Latest papers with no code
Boosting Skull-Stripping Performance for Pediatric Brain Images
With the emergence of multi-institutional pediatric data acquisition efforts to broaden the understanding of perinatal brain development, it is essential to develop robust and well-tested tools ready for the relevant data processing.
Longitudinal Volumetric Study for the Progression of Alzheimer's Disease from Structural MRI
Alzheimer's Disease (AD) is an irreversible neurodegenerative disorder affecting millions of individuals today.
Brain MRI Segmentation using Template-Based Training and Visual Perception Augmentation
Deep learning models usually require sufficient training data to achieve high accuracy, but obtaining labeled data can be time-consuming and labor-intensive.
Attention-based convolutional neural network for perfusion T2-weighted MR images preprocessing
Accurate skull-stripping is crucial preprocessing in dynamic susceptibility contrast-enhanced perfusion magnetic resonance data analysis.
Performance Evaluation of Vanilla, Residual, and Dense 2D U-Net Architectures for Skull Stripping of Augmented 3D T1-weighted MRI Head Scans
Skull Stripping is a requisite preliminary step in most diagnostic neuroimaging applications.
Wide Range MRI Artifact Removal with Transformers
Our method is realized through the design of a novel volumetric transformer-based neural network that generalizes a \emph{window-centered} approach popularized by the Swin transformer.
Detection and Classification of Brain tumors Using Deep Convolutional Neural Networks
Tumour in the brain is fatal as it may be cancerous, so it can feed on healthy cells nearby and keep increasing in size.
k-strip: A novel segmentation algorithm in k-space for the application of skull stripping
Results: Both datasets were very similar to the ground truth (DICE scores of 92\%-98\% and Hausdorff distances of under 5. 5 mm).
SynthStrip: Skull-Stripping for Any Brain Image
The removal of non-brain signal from magnetic resonance imaging (MRI) data, known as skull-stripping, is an integral component of many neuroimage analysis streams.
Plug-and-play Shape Refinement Framework for Multi-site and Lifespan Brain Skull Stripping
For instance, the model trained on a dataset with specific imaging parameters cannot be well applied to other datasets with different imaging parameters.