Interactive segmentation framework of the Medical Imaging Interaction Toolkit

Abstract

Interactive methods are indispensable for real world applications of segmentation in medicine, at least to allow for convenient and fast verification and correction of automated techniques. Besides traditional interactive tasks such as adding or removing parts of a segmentation, adjustment of contours or the placement of seed points, the relatively recent Graph Cut and Random Walker segmentation methods demonstrate an interest in advanced interactive strategies for segmentation. Though the value of toolkits and extensible applications is generally accepted for the development of new segmentation algorithms, the topic of interactive segmentation applications is rarely addressed by current toolkits and applications. In this paper, we present the extension of the Medical Imaging Interaction Toolkit (MITK) with a framework for the development of interactive applications for image segmentation. The framework provides a clear structure for the development of new applications and offers a plugin mechanism to easily extend existing applications with additional segmentation tools. In addition, the framework supports shape-based interpolation and multi-level undo/redo of modifications to binary images. To demonstrate the value of the framework, we also present a free, open-source application named InteractiveSegmentation for manual segmentation of medical images (including 3D+t), which is built based on the extended MITK framework. The application includes several features to effectively support manual segmentation, which are not found in comparable freely available applications. InteractiveSegmentation is fully developed and successfully and regularly used in several projects. Using the plugin mechanism, the application enables developers of new algorithms to begin algorithmic work more quickly.