Automatic Fetal Measurements in Ultrasound Using Constrained Probabilistic Boosting Tree

Abstract. Automatic delineation and robust measurement of fetal anatomical structures in 2D ultrasound images is a challenging task due to the complexity of the object appearance, noise, shadows, and quantity of information to be processed. Previous solutions rely on explicit encoding of prior knowledge and formulate the problem as a perceptual grouping task solved through clustering or variational approaches. These methods are known to be limited by the validity of the underlying assumptions and cannot capture complex structure appearances. We propose a novel system for fast automatic obstetric measurements by directly exploiting a large database of expert annotated fetal anatomical structures in ultrasound images. Our method learns to distinguish between the appearance of the object of interest and background by training a discriminative constrained probabilistic boosting tree classifier. This system is able to handle previously unsolved problems in this domain, such as the effective...

• Type: Conference
• Year: 2007
• Where: MICCAI
• Authors: Gustavo Carneiro, Bogdan Georgescu, Sara Good, Dorin Comaniciu
• Keywords: Automatic Obstetric Measurements, Fetal Abdomens, Fetal Anatomical Structures, Medical Imaging, MICCAI 2007