TY - JOUR
AU - Saeed, N.
AB - This review highlights various magnetic resonance image (MRI) segmentation algorithms that employ pattern recognition. The procedures are grouped into two categories: low‐ to intermediate‐level, and high‐level image processing. The former consists of grey level histogram analysis, texture definition, edge identification, region growing, and contour following. The roles of significant prior knowledge, neural networks and cluster analysis are examined by producing objective identification of anatomical structures. The application of the segmented anatomical structures in image registration, to monitor the disease progression or growth of anatomy in normal volunteers and patients, is highlighted. The use of the segmented anatomy in measuring volumes of structures in normals and patients is also examined.
TI - Magnetic resonance image segmentation using pattern recognition, and applied to image registration and quantitation
JF - NMR in Biomedicine
DO - 10.1002/(SICI)1099-1492(199806/08)11:4/5<157::AID-NBM528>3.0.CO;2-L
DA - 1998-06-01
UR - https://www.deepdyve.com/lp/wiley/magnetic-resonance-image-segmentation-using-pattern-recognition-and-8rBH0eXkV4
SP - 157
EP - 167
VL - 11
IS - 4‐5
DP - DeepDyve
ER -