Automatic Initialization of Contour for Level Set Algorithms Guided by Integration of Multiple Views to Segment Abdominal CT Scans

Abstract—This paper presents a new automatic initialization procedure for a level-set based segmentation algorithm that works on all slices for a given CT dataset. Level set segmentation algorithms provide promising results, are robust to dataset variations and do not require prior training. As such, they can be reliably used for segmentation of major organs in abdominal CT scans. However, level set algorithms still require user intervention to plot the initial contour for each slice in a given dataset, which is a time consuming process. Therefore, we propose here, a technique of using multiple views to automatically initialize and propagate the contour through each slice in the CT dataset. The technique requires a user to only initialize a single point within the organ of interest in order to initiate the automated segmentation process. We report the segmentation results for liver and spleen organs within the abdominal region using three different datasets. We conclude that this technique can be used to reduce the processing time for any level set algorithm suitable to abdominal CT scans. We typically achieve time efficiency up to 203.03 % for complete segmentation of three organs as compared to manually initializing the level set contour for each slice. Keywords-automatic initialization; mutliple views integration; level set active contour; abdominal CT images; medical knowledge. I