Atlas-based segmentation of abdominal organs in 3D ultrasound, and its application in automated kidney segmentation.

Automated segmentation of abdominal organs in 3D ultrasound images is an important and challenging task toward computer assisted emergency diagnosis. However, speckle noise, low-contrast organ tissues, intensity-profile inhomogeneity, and partial organ visibility are some ultrasound challenges which limits the utility of the automated diagnosis solutions. In this paper, an atlas-based method to automatically segment an organ of interest in abdominal 3D ultrasound images is proposed. The atlas model contains texture information and shape knowledge of the organ, which facilitates an accurate discrimination of organ from non-organ voxels in input 3D ultrasound images. The proposed method offers a mechanism to automatically detect the organ, and therefore, it eliminates the need of manual initialization of organ segmentation. The proposed method is applied to automatically segment the right kidney in 3D ultrasound images. The experimental results indicate that the proposed method provides a higher detection and segmentation accuracy compared to state-of-the-art.