Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  compare a representative selection of current state-of-the-art algorithms in diffusion-ighted magnetic resonance imaging (dwMRI) tractography, and propose a novel way to quantitatively define the connectivity beten brain regions. As criterion for the comparison,  quantify the connectivity computed with the different methods.  provide initial results using diffusion tensor, spherical deconvolution, ball-and-stick model, and persistent angular structure (PAS) along with deterministic and probabilistic tractography algorithms on a human DWI dataset. The connectivity is presented for a representative selection of regions in the brain in matrices and connectograms.Our results show that fiber crossing models are able to reveal connections beten more brain areas than the simple tensor model. Probabilistic approaches show in average more connected regions but lor connectivity values than deterministic methods.
['Ting-Shuo Yo', 'Alfred Anwander', 'Maxime Descoteaux', 'Pierre Fillard', 'Cyril Poupon', 'Thomas R. Knösche']
I am writing a research paper on a idea Quantifying Brain Connectivity: A Comparative Tractography Study
[{"from": "human", "value": "I am writing a research paper on a idea Quantifying Brain Connectivity: A Comparative Tractography Study"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely: ,  compare a representative selection of current state-of-the-art algorithms in diffusion-ighted magnetic resonance imaging (dwMRI) tractography, and propose a novel way to quantitatively define the connectivity beten brain regions. As criterion for the comparison,  quantify the connectivity computed with the different methods.  provide initial results using diffusion tensor, spherical deconvolution, ball-and-stick model, and persistent angular structure (PAS) along with deterministic and probabilistic tractography algorithms on a human DWI dataset. The connectivity is presented for a representative selection of regions in the brain in matrices and connectograms.Our results show that fiber crossing models are able to reveal connections beten more brain areas than the simple tensor model. Probabilistic approaches show in average more connected regions but lor connectivity values than deterministic methods."}]