Multimedia Medical Databases

A comparative study of some methods for color medical images segmentation

“…Image segmentation is defined as the partitioning of an image into no overlapping, constituent regions that are homogeneous, taking into consideration some characteristic such as intensity or texture [1,2].…”

“…There have been studied several segmentation methods that are influenced by factors such as application domain, imaging modality, or others [1,2,10].…”

“…Classifiers are known as supervised methods because they need training data that are manually segmented by medical experts and then used as references for automatically segmenting new data [1,2].…”

“…Because there is not any training data, clustering methods iterate between segmenting the image and characterizing the properties of each class. It can be said that clustering methods train themselves using the available data [1,2,12,13].…”

“…This task is vital in many biomedical imaging applications such as the quantification of tissue volumes, diagnosis, localization of pathology, study of anatomical structure, treatment planning, partial volume correction of functional imaging data, and computer-integrated surgery [1,2].…”