Medical image segmentation is nowadays required for medical device development and in a growing number of clinical and research applications. Since dedicated automatic segmentation methods are not always available, generic and efficient interactive tools can alleviate the burden of manual segmentation. In this paper we propose an interactive segmentation tool based on image warping and minimal path segmentation that is efficient for a wide variety of segmentation tasks. While the user roughly delineates the desired organs boundary, a narrow band along the cursors path is straightened, providing an ideal subspace for feature aligned filtering and minimal path algorithm. Once the segmentation is performed on the narrow band, the path is warped back onto the original image, precisely delineating the desired structure. This tool was found to have a highly intuitive dynamic behavior. It is especially efficient against misleading edges and required only coarse interaction from the user to achieve good precision. The proposed segmentation method was tested for 10 difficult liver segmentations on CT and MRI images, and the resulting 2D overlap Dice coefficient was 99% on average..
This paper proposes a prior shape segmentation method to create a constant-width ribbon-like zone that runs
along the boundary to be extracted. The image data corresponding to that zone is transformed into a rectangular
image subspace where the boundary is roughly straightened. Every step of the segmentation process
is then applied to that straightened subspace image where the final extracted boundary is transformed back
into the original image space. This approach has the advantage of producing very efficient filtering and edge
detection using conventional techniques. The final boundary is continuous even over image regions where partial
information is missing. The technique was applied to the femoral head segmentation where we show that the
final segmented boundary is very similar to the one obtained manually by a trained orthopedist and has low
sensitivity to the initial positioning of the prior shape.