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Abstract #2398

A Deep k-means Based Tissue Extraction from Reconstructed Human Brain MR Image

Madiha Arshad1, Mahmood Qureshi1, Omair Inam1, and Hammad Omer1
1Medical Image Processing Research Group (MIPRG), Department of Electrical and Computer Engineering, COMSATS University, Islamabad, Pakistan

Fast and accurate tissue extraction of human brain is an ongoing challenge. Two principal factors make this task difficult:(1) quality of the reconstructed images, (2) accuracy and availability of the segmentation masks. In this proposed method, firstly, a supervised deep learning framework is used for the reconstruction of solution image from the acquired uniformly under-sampled human brain data. Later, an unsupervised clustering approach i.e. k-means is used for the extraction of specific tissue from the reconstructed image. Experimental results show a successful extraction of cerebrospinal fluid (CSF), white matter and grey matter from the human brain image.

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