使用二维主动形状模型从超声图像中进行三维前列腺边界分割。

3D prostate boundary segmentation from ultrasound images using 2D active shape models.

作者信息

Hodge Adam C, Ladak Hanif M

机构信息

Department of Medical Biophysics, The University of Western Ontario, London, Canada.

出版信息

Conf Proc IEEE Eng Med Biol Soc. 2006;2006:2337-40. doi: 10.1109/IEMBS.2006.260668.

DOI:10.1109/IEMBS.2006.260668

PMID:17946106

Abstract

Boundary outlining, or segmentation, of the prostate is an important task in diagnosis and treatment planning for prostate cancer. This paper describes an algorithm for semi-automatic, three-dimensional (3D) segmentation of the prostate boundary from ultrasound images based on two-dimensional (2D) active shape models (ASM) and rotation-based slicing. Evaluation of the algorithm used distance- and volume-based error metrics to compare algorithm generated boundary outlines to gold standard (manually generated) boundary outlines. The mean absolute distance between the algorithm and gold standard boundaries was 1.09+/-0.49 mm, the average percent absolute volume difference was 3.28+/-3.16%, and a 5x speed increase as compared manual planimetry was achieved.

摘要

前列腺边界勾勒，即分割，在前列腺癌的诊断和治疗规划中是一项重要任务。本文描述了一种基于二维主动形状模型（ASM）和基于旋转切片的算法，用于从超声图像中半自动三维（3D）分割前列腺边界。该算法的评估使用了基于距离和体积的误差度量，以将算法生成的边界轮廓与金标准（手动生成）边界轮廓进行比较。算法与金标准边界之间的平均绝对距离为1.09±0.49毫米，平均绝对体积百分比差异为3.28±3.16%，并且与手动平面测量相比速度提高了5倍。