Region-growing based image segmentation techniques, available for medical images, are reviewed in this paper. In digital image processing, segmentation of humans' organs from medical images is a very challenging task. A number of medical image segmentation techniques have been proposed, but there is no standard automatic algorithm that can generally be used to segment a real 3D image obtained in daily routine by the clinicians. Our criteria for the evaluation of different region-growing based segmentation algorithms are: ease of use, noise vulnerability, effectiveness, need of manual initialization, efficiency, computational complexity, need of training, information used, and noise vulnerability. We test the common region-growing algorithms on a set of abdominal MRI scans for the aorta segmentation. The evaluation results of the segmentation algorithms show that region-growing techniques can be a better choice for segmenting an object of interest from medical images.