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Found 8 papers, 1 papers with code
Preserving Derivative Information while Transforming Neuronal Curves
Then, the traces are mapped to common coordinate systems by transforming the positions of their points, which neglects how the transformation bends the line segments in between.
Hidden Markov Modeling for Maximum Likelihood Neuron Reconstruction
Our most probable estimation method models the task of reconstructing neuronal processes in the presence of other neurons, and thus is applicable in images with several neurons.
Fitting Splines to Axonal Arbors Quantifies Relationship between Branch Order and Geometry
Our representation makes it possible to compute these parameters from neuron traces in closed form.
A Community-Developed Open-Source Computational Ecosystem for Big Neuro Data
Big imaging data is becoming more prominent in brain sciences across spatiotemporal scales and phylogenies.
Neurons and Cognition Quantitative Methods
NeuroStorm: Accelerating Brain Science Discovery in the Cloud
Neuroscientists are now able to acquire data at staggering rates across spatiotemporal scales.
A Large Deformation Diffeomorphic Approach to Registration of CLARITY Images via Mutual Information
Due to the novelty of this microscopy technique it is impractical to use absolute intensity values to align these images to existing standard atlases.
Deformably Registering and Annotating Whole CLARITY Brains to an Atlas via Masked LDDMM
Therefore, we developed a method (Mask-LDDMM) for registering CLARITY images, that automatically find the brain boundary and learns the optimal deformation between the brain and atlas masks.
