SU-E-J-106: Atlas-Based Segmentation: Evaluation of a Multi-Atlas Approach for Lung Cancer

Medical Physics
S PirozziA Nelson

Abstract

Previous studies have shown atlas-based segmentation using a single best matched (SBM) atlas subject can significantly reduce contouring time. A new multi-atlas approach has been shown to provide greater accuracy than SBM for cancer of the head and neck. The goal of this study was to evaluate the multi-atlas technique for lung cancer treatment planning. An institution's SBRT lung atlas containing 82 subjects was utilized for atlas segmentation. Each atlas subject contained manually defined contours of the esophagus, cord, heart, left lung, right lung, and trachea. CT scans and contours for 16 subjects were evaluated. SBM used the one automatically determined best match for segmentation. Multi-atlas used multiple automatically determined best matches: 3, 4, and 5, respectively. The final segmentation for multi-atlas was generated using Majority Vote which comprises the area of overlap for at least half of the individual segmentations (2 of 3, 2 of 4, and 3 of 5, respectively). Average Dice Similarity Coefficients (DSC) were calculated for each structure to compare against manually defined 'gold' standard contours for that subject. Overall percent improvement was calculated as the proportion of the error corrected by the method, ...Continue Reading

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