Papers Brain Morphometry
“Brain Morphometry” 태그가 달린 논문 9편 · 필터 해제
Dataset Properties Shape the Success of Neuroimaging-Based Patient Stratification: A Benchmarking Analysis Across Clustering Algorithms
Background: Data driven stratification of patients into biologically informed subtypes holds promise for precision neuropsychiatry, yet neuroimaging-based clustering methods often fail to generalize across cohorts. While…
BenchmarkingBrain MorphometryRicci flow-based brain surface covariance descriptors for diagnosing Alzheimer's disease
Automated feature extraction from MRI brain scans and diagnosis of Alzheimer's disease are ongoing challenges. With advances in 3D imaging technology, 3D data acquisition is becoming more viable and efficient than its 2D…
Brain MorphometryFast refacing of MR images with a generative neural network lowers re-identification risk and preserves volumetric consistency
With the rise of open data, identifiability of individuals based on 3D renderings obtained from routine structural magnetic resonance imaging (MRI) scans of the head has become a growing privacy concern. To protect subje…
Brain MorphometryDe-identificationFace GenerationGenerative Adversarial NetworkReliable brain morphometry from contrast‐enhanced T1w‐MRI in patients with multiple sclerosis
Brain morphometry is usually based on non-enhanced (pre-contrast) T1-weighted MRI. However, such dedicated protocols are sometimes missing in clinical examinations. Instead, an image with a contrast agent is often availa…
3D Medical Imaging SegmentationAnatomyBrain MorphometryBrain Segmentation+3Multiple Instance Neuroimage Transformer
For the first time, we propose using a multiple instance learning based convolution-free transformer model, called Multiple Instance Neuroimage Transformer (MINiT), for the classification of T1weighted (T1w) MRIs. We fir…
Brain MorphometryMultiple Instance LearningDirect cortical thickness estimation using deep learning‐based anatomy segmentation and cortex parcellation
Accurate and reliable measures of cortical thickness from magnetic resonance imaging are an important biomarker to study neurodegenerative and neurological disorders. Diffeomorphic registration‐based cortical thickness (…
3D Medical Imaging SegmentationAnatomyBrain MorphometryBrain Segmentation+2Going deeper with brain morphometry using neural networks
Brain morphometry from magnetic resonance imaging (MRI) is a consolidated biomarker for many neurodegenerative diseases. Recent advances in this domain indicate that deep convolutional neural networks can infer morphomet…
Brain MorphometryEfficient Neural NetworkBrain Morphometry Estimation: From Hours to Seconds Using Deep Learning
Motivation: Brain morphometry from magnetic resonance imaging (MRI) is a promising neuroimaging biomarker for the non-invasive diagnosis and monitoring of neurodegenerative and neurological disorders. Current tools for b…
Brain MorphometryDeep LearningregressionPersistent Homology in Sparse Regression and Its Application to Brain Morphometry
Sparse systems are usually parameterized by a tuning parameter that determines the sparsity of the system. How to choose the right tuning parameter is a fundamental and difficult problem in learning the sparse system. In…
Brain Morphometryregression