@inproceedings{0ecc5c65df7e4d3caf8643ce29d86721,
title = "Automatic 3D segmentation of ultrasound images using atlas registration and statistical texture prior",
abstract = "We are developing a molecular image-directed, 3D ultrasound-guided, targeted biopsy system for improved detection of prostate cancer. In this paper, we propose an automatic 3D segmentation method for transrectal ultrasound (TRUS) images, which is based on multi-atlas registration and statistical texture prior. The atlas database includes registered TRUS images from previous patients and their segmented prostate surfaces. Three orthogonal Gabor filter banks are used to extract texture features from each image in the database. Patient-specific Gabor features from the atlas database are used to train kernel support vector machines (KSVMs) and then to segment the prostate image from a new patient. The segmentation method was tested in TRUS data from 5 patients. The average surface distance between our method and manual segmentation is 1.61 ± 0.35 mm, indicating that the atlas-based automatic segmentation method works well and could be used for 3D ultrasound-guided prostate biopsy.",
keywords = "Atlas registration, Automatic 3D segmentation, Gabor filter, Prostate cancer, Support vector machine, Ultrasound imaging",
author = "Xiaofeng Yang and David Schuster and Viraj Master and Peter Nieh and Aaron Fenster and Baowei Fei",
year = "2011",
doi = "10.1117/12.877888",
language = "English (US)",
isbn = "9780819485069",
series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",
booktitle = "Medical Imaging 2011",
note = "Medical Imaging 2011: Visualization, Image-Guided Procedures, and Modeling ; Conference date: 13-02-2011 Through 15-02-2011",
}