Stefan Lautenschläger

Esophagus Segmentation by Spatially-Constrained Shape Interpolation

The segmentation and visualization of the esophagus is helpful during planing and performing atrial ablation therapy to avoid esophageal injury. Only very few studies have addressed this segmentation problem which is challenging because the esophagus has a low contrast in medical images. In this work we present a technique to segment the esophagus based on the interpolation of Fourier descriptors of manually drawn contours. The interpolation is spatially-constrained using a dedicated correction term to avoid intersections with the convex shaped left atrial posterior wall. Our technique is fast, modality independent and achieves optimal results if at least three input contours are used. We validated our technique successfully with patient data and discuss the use of our technique in the clinical workflow.

Automatic Detection of Air Holes Inside the Esophagus in CT Images

Air holes inside the esophagus can be used to localize the esophagus in computed tomographic (CT) images. In this work we present a technique to automatically detect esophageal air holes in this modality. Our technique is based on the extraction of a volume of interest, air segmentation by thresholding and classification of respiratory and esophageal air using a priori knowledge about the connectivity of air voxels. A post-processing step rejects wrong results from artifacts in the CT image. We successfully tested our algorithm with clinical data and compared the detection results of a human expert and our technique.