Shao Fan, Ling Keck Voon, Ng Wan Sing, Wu Ruo Yun
School of Electrical and Electroni Engineering, Nanyang Technological University, 50 Nanyang Ave, Singapore 639798.
J Ultrasound Med. 2003 Jun;22(6):605-23. doi: 10.7863/jum.2003.22.6.605.
Prostate diseases are very common in adult and elderly men, and prostate boundary detection from ultrasonographic images plays a key role in prostate disease diagnosis and treatment. However, because of the poor quality of ultrasonographic images, prostate boundary detection still remains a challenging task. Currently, this task is performed manually, which is arduous and heavily user dependent. To improve the efficiency by automating the boundary detection process, numerous methods have been proposed. We present a review of these methods, aiming to find a good solution that could efficiently detect the prostate boundary on ultrasonographic images.
A full description of various methods is beyond the scope of this article; instead, we focus on providing an introduction to the different methods with a discussion of their advantages and disadvantages. Moreover, verification methods for estimating the accuracies of the algorithms reported in the literature are discussed as well.
From the investigation, we summarize several key issues that might be confronted and project possible future research.
Those model-based methods that minimize user involvement but allow for interactive guidance of experts will likely be most immediately successful.
前列腺疾病在成年男性和老年男性中非常常见,从超声图像中检测前列腺边界在前列腺疾病的诊断和治疗中起着关键作用。然而,由于超声图像质量较差,前列腺边界检测仍然是一项具有挑战性的任务。目前,这项任务是手动完成的,既费力又严重依赖用户。为了通过自动化边界检测过程提高效率,已经提出了许多方法。我们对这些方法进行综述,旨在找到一种能够有效检测超声图像上前列腺边界的良好解决方案。
对各种方法进行全面描述超出了本文的范围;相反,我们专注于对不同方法进行介绍,并讨论它们的优缺点。此外,还讨论了文献中报道的用于估计算法准确性的验证方法。
通过调查,我们总结了可能面临的几个关键问题,并预测了未来可能的研究方向。
那些基于模型的方法,在尽量减少用户参与的同时允许专家进行交互式指导,可能会立即取得最大成功。