The watershed algorithm: a method to segment noisy PET transmission images

Abstract

Attenuation correction is essential to PET imaging but often requires impractical acquisition times. Segmentation of short, noisier transmission scans has been proposed as a solution. We report that a 3D morphological tool-the watershed algorithm-is well adapted for segmenting even two-minute PET transmission images. The technique is non-iterative, fast and fully 3D. It inherently ensures class continuity and eliminates outliers. Pre-filtering the data induced smoother class edges, showing that a multi-resolution approach could be used to deal with the partial volume effect and excessive noise in the data. The algorithm was tested on two-minute scans of a torso phantom and on a human study.

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