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dhirajmaji7 / QuickNAT-keras

Implementation of QuickNAT for brain tumor segmentation using Keras library with tensorflow as backend. The QuickNAT is a fast and accurate segmentation model. The model has been implemented along with the Unpooling and a combined loss function of dice score and weighted cross-entropy as described in the paper.

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request this code's paper! #1

Open han-yeol opened 3 years ago

han-yeol commented 3 years ago

Hello! I am interested in your implementation. can I request your code's original paper?

dhirajmaji7 commented 3 years ago

Abhijit Guha Roy, Sailesh Conjeti, Nassir Navab, Christian Wachinger. QuickNAT: A fully convolutional network for quick and accurate segmentation of neuroanatomy, NeuroImage, Volume 186, 2019, Pages 713-727, ISSN 1053-8119, https://doi.org/10.1016/j.neuroimage.2018.11.042

han-yeol commented 3 years ago

Did you use .nii files? or npy files? also what did you use any preprocessing process?