Cortical thickness

Outline: In this challenge you will develop an algorithm to estimate cortical thickness map from a raw T1-weighted image. Cortical thickness map is the thickness of the gray matter of the brain at every point. It is defined as the distance between the white matter surface and the pial surface


• Use nibabel libraries to load nifti image into python

• You will probably want to segment the white matter first. This will give you the starting point for your thickness estimation algorithm.

• Once you have the white matter segmentation, decide how you will go about estimating thickness. Something like the following:

o Find a vector orthogonal to the white matter surface

o Cast the vector outwards

o Use some heuristic to decide where the vector meets the pial surface (cortical thickness is then given by vector length

Summary: load [login to view URL] into python. Segment the gray and white matter. Use some algorithm to find the cortical thickness at each point in the gray matter. Label all gray matter voxels with the cortical thickness value at that point. Output the labeled image (like in figure 02).

Навыки: Алгоритмы, Математика, Python, NumPy, Machine Learning (ML)

О клиенте:
( 0 отзыв(-а, -ов) ) Mumbai, India

ID проекта: #33970276

2 фрилансеров(-а) готовы выполнить эту работу в среднем за ₹5300


Implementing projects using Python and Machine Learning is our core forte since we are working on it for more than 5+ years now. We are a team of 50+ developers who have successfully delivered 350+ Machine Learning Pro Больше

₹7000 INR за 7 дней(-я)
(5 отзывов(-а))

Hello, I noticed your project and I would like to be hired for it. I'm currently a Ph.D student. I'm working on Machine Learning and Data Analysis. I have solid expertise in the domain. Quality and time of the work wil Больше

₹3600 INR за 5 дней(-я)
(2 отзывов(-а))