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Found 5 papers, 1 papers with code
PyCellMech: A shape-based feature extraction pipeline for use in medical and biological studies
The significance of shape-based features has been explored extensively in research for several decades, but there is no single package available in which all shape-related features can be extracted easily by the researcher.
Multi-Center Fetal Brain Tissue Annotation (FeTA) Challenge 2022 Results
The FeTA Challenge 2022 was able to successfully evaluate and advance generalizability of multi-class fetal brain tissue segmentation algorithms for MRI and it continues to benchmark new algorithms.
Frequency Disentangled Learning for Segmentation of Midbrain Structures from Quantitative Susceptibility Mapping Data
One may hypothesize that such property can be leveraged for better training of deep learning models.
Fourier Disentangled Multimodal Prior Knowledge Fusion for Red Nucleus Segmentation in Brain MRI
In this paper, we propose a new model that integrates prior knowledge from different contrasts for red nucleus segmentation.
Learning brain MRI quality control: a multi-factorial generalization problem
We further analyzed the site-wise and study-wise predicted classification probability distributions of the models without preprocessing trained on ABIDE and CATI data.
