An Overview on Interactive Medical Image Segmentation

Abstract

Image segmentation is often described as partitioning an image into a finite number of semantically non-overlapping regions. In medical applications, it is a fundamental process in most systems that support medical diagnosis, surgical planning and treatments. Generally, this process is done manually by clinicians, which may be time-consuming and tedious. To alleviate the problem, a number of interactive segmentation methods have been proposed in the literature. These techniques take advantage of automatic segmentation and allow users to intervene the segmentation process by incorporating prior-knowledge, validating results and correcting errors, thus potentially lead to accurate segmentation results. In this paper, we present an overview on interactive segmentation techniques for medical images