NeuroLOTs is a set of libraries and tools that implement a method for generating neuronal meshes and for visualizing them at different levels of detail using GPU-based tessellation. As a part of NeuroLOTs, NeuroTessMesh provides a visual environment for the generation of 3D polygonal meshes that approximate the membrane of neuronal cells, from the morphological tracings that describe the morphology of the neurons. The 3D models can be tessellated at different levels of detail, providing either homogeneous or adaptive resolution along the model. The soma shape is recovered from the incomplete information of the tracings, applying a physical deformation model that can be interactively adjusted. The adaptive refinement process performed in the GPU generates meshes that allow good visual quality geometries at an affordable computational cost, both in terms of memory and rendering time. NeuroTessMesh is the front-end GUI to NeuroLOTs framework.
NeuroTessMesh source code is available through GIT repository at https://github.com/vg-lab/neurotessmesh
NeuroLOTs source code is available through GIT repository at https://github.com/vg-lab/neurolots
Binary executables for the latest release of NeuroTessMesh are available for Windows and Linux.
Important note: the application requires a graphic card that supports OpenGL 4.0 at least. NVIDIA offers support for GPU tessellation from the GTX 400 series on, and ATI/AMD from Radeon HD 5000 series on. Previous series of both companies are not able to tessellate and consequently the mesh refinement will not work. The GPU Tessellation on Intel graphics cards is present only on certain models, for more information you can visit the next link: Supported APIs and Features for Intel® Graphics Drivers.
Docker images for NeuroTessMesh are publicly available in Docker Hub
This work has been partially supported by the Spanish Ministry of Economy and Competitiveness (Grants TIN2014-57481 and BFU2013-41533R, and the Cajal Blue Brain Project C080020-09, the Spanish partner of the Blue Brain initiative from EPFL) and by the European Union’s Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 604102 (Human Brain Project).