Generative Sampling in Bundle Tractography using Autoencoders (GESTA)

Author:

Legarreta Jon HaitzORCID,Petit LaurentORCID,Jodoin Pierre-MarcORCID,Descoteaux MaximeORCID

Publisher

Elsevier BV

Subject

Computer Graphics and Computer-Aided Design,Health Informatics,Computer Vision and Pattern Recognition,Radiology, Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Reference54 articles.

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2. A reproducible evaluation of ANTs similarity metric performance in brain image registration;Avants;NeuroImage,2011

3. Improving tractography accuracy using dynamic filtering;Battocchio,2020

4. Bundle-o-graphy;Battocchio,2021

5. Representation learning: A review and new perspectives;Bengio;IEEE Trans. Pattern Anal. Mach. Intell.,2013

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1. Bounding tractogram redundancy;Frontiers in Neuroscience;2024-07-23

2. Differentiable VQ-VAE’s for Robust White Matter Streamline Encodings;2024 IEEE International Symposium on Biomedical Imaging (ISBI);2024-05-27

3. FIESTA: Autoencoders for accurate fiber segmentation in tractography;NeuroImage;2023-10

4. Variational Autoencoders for Generating Synthetic Tractography-Based Bundle Templates in a Low-Data Setting;2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC);2023-07-24

5. Deep Learning Methods for Identification of White Matter Fiber Tracts: Review of State-of-the-Art and Future Prospective;Neuroinformatics;2023-06-17

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