@inproceedings{3968399453d0496a8419452ff1e0a422,
title = "Measurement of thermally ablated lesions in sonoelastographic images using level set methods",
abstract = "The capability of sonoelastography to detect lesions based on elasticity contrast can be applied to monitor the creation of thermally ablated lesion. Currently, segmentation of lesions depicted in sonoelastographic images is performed manually which can be a time consuming process and prone to significant intra- and inter-observer variability. This work presents a semi-automated segmentation algorithm for sonoelastographic data. The user starts by planting a seed in the perceived center of the lesion. Fast marching methods use this information to create an initial estimate of the lesion. Subsequently, level set methods refine its final shape by attaching the segmented contour to edges in the image while maintaining smoothness. The algorithm is applied to in vivo sonoelastographic images from twenty five thermal ablated lesions created in porcine livers. The estimated area is compared to results from manual segmentation and gross pathology images. Results show that the algorithm outperforms manual segmentation in accuracy, inter- and intra-observer variability. The processing time per image is significantly reduced.",
keywords = "Elasticity, Fast marching methods, Image processing, Level set methods, Mumford-Shah functional, Region growing, Segmentation, Sonoelastography",
author = "Benjamin Castaneda and Tamez-Pena, {Jose Gerardo} and Man Zhang and Kenneth Hoyt and Kevin Bylund and Jared Christensen and Wael Saad and John Strang and Rubens, {Deborah J.} and Parker, {Kevin J.}",
year = "2008",
doi = "10.1117/12.770811",
language = "English",
isbn = "9780819471048",
series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",
booktitle = "Medical Imaging 2008",
note = "Medical Imaging 2008: Ultrasonic Imaging and Signal Processing ; Conference date: 17-02-2008 Through 18-02-2008",
}