4 papers
Tractography-Driven Synthetic Data Generation for Fiber Bundle Segmentation in Tracer Histology
Kyriaki-Margarita Bintsi, Sparsh Makharia, Yaël Balbastre +4
Diffusion MRI (dMRI) tractography enables non-invasive reconstruction of white-matter pathways, but its accuracy is fundamentally limited by indirect, low-resolution measurements o…
Learn2Synth: Learning Optimal Data Synthesis Using Hypergradients for Brain Image Segmentation
Xiaoling Hu, Xiangrui Zeng, Oula Puonti +3
Domain randomization through synthesis is a powerful strategy to train networks that are unbiased with respect to the domain of the input images. Randomization allows networks to s…
Neurovascular Segmentation in sOCT with Deep Learning and Synthetic Training Data
Etienne Chollet, Yaël Balbastre, Chiara Mauri +3
Microvascular anatomy is known to be involved in various neurological disorders. However, understanding these disorders is hindered by the lack of imaging modalities capable of cap…
A label-free and data-free training strategy for vasculature segmentation in serial sectioning OCT data
Etienne Chollet, Yael Balbastre, Caroline Magnain +2
Serial sectioning Optical Coherence Tomography (sOCT) is a high-throughput, label free microscopic imaging technique that is becoming increasingly popular to study post-mortem neur…