Grau, V., Kikinis, R., Alcaniz, M. and Wareld, S.K. (2003) Cortical Gray Matter Segmentation Using an Improved Watershed Transforms. Surgical Planning Laboratory, Brigham and Women’s Hospital, Harvard Medical School. Proceedings of the 25th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 17-21 Sept. 2003, Vol. 1, 618-621.
http://dx.doi.org/10.1109/iembs.2003.1279828

has been cited by the following article:

• TITLE: Computerized White Matter and Gray Matter Extraction from MRI of Brain Image

  AUTHORS: Sudipta Roy, Debayan Ganguly, Kingshuk Chatterjee, Samir Kumar Bandyopadhyay

  KEYWORDS: Automated Segmentation, Convexhull, Relative Area, White Matter, Gray Matter, Standard Deviation

  JOURNAL NAME: Journal of Biomedical Science and Engineering, Vol.8 No.9, September 4, 2015

  ABSTRACT: Automated segmentation of white matter (WM) and gray matter (GM) is a very important task for detecting multiple diseases. The paper proposed a simple method for WM and GM extraction form magnetic resonance imaging (MRI) of brain. The proposed methods based on binarization, wavelet decomposition, and convexhull produce very effective results in the context of visual inspection and as well as quantifiably. It tested on three different (Transvers, Sagittal, Coronal) types of MRI of brain image and the validation of experiment indicate accurate detection and segmentation of the interesting structures or particular region of MRI of brain image.