Title :
Cortical gray matter segmentation using an improved watershed-transform
Author :
Grau, Vicente ; Kikinis, Ron ; Alcaniz, Mariano ; Warfield, Simon K.
Author_Institution :
Brigham & Women´´s Hosp., Harvard Med. Sch., Boston, MA, USA
Abstract :
An accurate segmentation of white matter, gray matter and cerebrospinal fluid (CSF) in MR images of the brain is key to understanding important brain diseases. We present a new system for segmentation of MR images of the brain, based on a novel modification of the watershed transform. Our proposed improvement is to substitute the single contour detection function (usually the gradient) of the original watershed transform with a set of functions especially tailored for the detection of each structure in the image. In this paper, these functions are based on a previous probability calculation, using normal distributions and a Markov Random Field. To improve the detection of the sulci, where the partial volume effect often masks the presence of CSF, the probability values for gray matter and CSF are modified using the absolute value of the distance to the white matter and the ridgeness of this distance. We also propose a novel way to initialize the watershed transform by using a probabilistic atlas: in this way, no user interaction is needed. Validation experiments indicate an accurate segmentation of the interesting structures.
Keywords :
biomedical MRI; brain; diseases; image segmentation; medical image processing; MR images; Markov random field; accurate segmentation; brain diseases; cerebrospinal fluid; cortical gray matter segmentation; improved watershed-transform; normal distributions; probabilistic atlas; single contour detection function; sulci detection; white matter segmentation; Alzheimer´s disease; Biomedical imaging; Gaussian distribution; Hospitals; Image segmentation; Laboratories; Markov random fields; Probability; Surface morphology; Surgery;
Conference_Titel :
Engineering in Medicine and Biology Society, 2003. Proceedings of the 25th Annual International Conference of the IEEE
Print_ISBN :
0-7803-7789-3
DOI :
10.1109/IEMBS.2003.1279828