Entangled Decision Forests and Their Application for Semantic Segmentation of CT Images

• Published in: Information Processing in Medical Imaging Vol. 22; pp. 184 - 196
• Main Authors: Montillo, Albert, Shotton, Jamie, Winn, John, Iglesias, Juan Eugenio, Metaxas, Dimitri, Criminisi, Antonio
• Format: Book Chapter Journal Article
• Language: English
• Published: Berlin, Heidelberg Springer Berlin Heidelberg 2011
• Series: Lecture Notes in Computer Science
• Subjects: Algorithms; Artificial Intelligence; auto-context; Cluster Analysis; decision forests; Entanglement; Humans; Pattern Recognition, Automated - methods; Radiographic Image Enhancement - methods; Radiographic Image Interpretation, Computer-Assisted - methods; Reproducibility of Results; segmentation; Sensitivity and Specificity; Tomography, X-Ray Computed - methods

This work addresses the challenging problem of simultaneously segmenting multiple anatomical structures in highly varied CT scans. We propose the entangled decision forest (EDF) as a new discriminative classifier which augments the state of the art decision forest, resulting in higher prediction acc...