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首页> 外文期刊>Computer Methods and Programs in Biomedicine: An International Journal Devoted to the Development, Implementation and Exchange of Computing Methodology and Software Systems in Biomedical Research and Medical Practice >Prostate boundary segmentation from ultrasound images using 2D active shape models: optimisation and extension to 3D.
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Prostate boundary segmentation from ultrasound images using 2D active shape models: optimisation and extension to 3D.

机译：使用2D活动形状模型从超声图像进行前列腺边界分割：优化和扩展到3D。

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摘要

Boundary outlining, or segmentation, of the prostate is an important task in diagnosis and treatment planning for prostate cancer. This paper describes an algorithm based on two-dimensional (2D) active shape models (ASM) for semi-automatic segmentation of the prostate boundary from ultrasound images. Optimisation of the 2D ASM for prostatic ultrasound was done first by examining ASM construction and image search parameters. Extension of the algorithm to three-dimensional (3D) segmentation was then done using rotational-based slicing. Evaluation of the 3D segmentation algorithm used distance- and volume-based error metrics to compare algorithm generated boundary outlines to gold standard (manually generated) boundary outlines. Minimum description length landmark placement for ASM construction, and specific values for constraints and image search were found to be optimal. Evaluation of the algorithm versus gold standard boundaries found an average mean absolute distance of 1.09+/-0.49 mm, an average percent absolute volume difference of 3.28+/-3.16%, and a 5x speed increase versus manual segmentation.
机译：前列腺的边界勾画或分割是前列腺癌的诊断和治疗计划中的重要任务。本文介绍了一种基于二维（2D）活动形状模型（ASM）的算法，用于从超声图像中半自动分割前列腺边界。首先通过检查ASM构造和图像搜索参数来完成2D ASM用于前列腺超声的优化。然后使用基于旋转的切片将算法扩展到三维（3D）分割。对3D分割算法的评估使用了基于距离和体积的错误度量，以将算法生成的边界轮廓与黄金标准（人工生成的）边界轮廓进行比较。发现用于ASM构造的最小描述长度地标放置以及约束和图像搜索的特定值是最佳的。对算法与黄金标准边界的评估发现，平均平均绝对距离为1.09 +/- 0.49 mm，平均绝对体积差百分比为3.28 +/- 3.16％，与手动分割相比，速度提高了5倍。

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