Background and objectives:Spina bifida is a fetal spine defect observed during pregnancy. The defect is caused by unfinished closure of the embryonic neural column. Common diagnosis of the defect is still based on manual examination which aims to detect any deformation on spinal axis. This study proposes a novel evolutionary method for locating spinal axis on sonograms of spina bifida pathology.

Methods: The method involves a meta-heuristic evolutionary approach, where the sonogram is automatically divided into columns and bone regions belonging to the spine are classified. Accordingly, a specific genetic algorithm is utilized which constructs a set of candidate spine axes. Fitness of the candidate axes is measured by a proposed problem-specific fitness function. A combination of conventional genetic operators and a novel energy minimization approach is applied to each population in order to explore the problem search space.

Results: Results show that presented algorithm is generally able to distinguish the spinal bones from others even in the presence of severe morphological defects.

Conclusion: It is observed that the presented approach is promising and in most samples the spines identified by the proposed algorithm closely match those drawn by the experts. A computer assisted ultrasound diagnosis system specialized for spina bifida cases does not exist yet, but an algorithm to identify the spine, such as the one presented in this work, is the first natural step towards a diagnosis system. In the future, we intend to improve the algorithm by improving the segmentation stage and further optimizing the various stages of the genetic algorithm.

背景和目的：脊柱裂是在怀孕期间观察到的胎儿脊柱缺陷。该缺陷是由于未完成胚胎神经柱的闭合引起的。缺陷的常见诊断仍基于手动检查，该检查旨在检测脊柱轴上的任何变形。这项研究提出了一种新的进化方法，用于在脊柱裂的病理超声图上定位脊柱轴。

方法：该方法涉及一种元启发式进化方法，该方法将超声图自动划分为列，并对属于脊柱的骨骼区域进行分类。因此，利用了特定的遗传算法，该算法构造了一组候选脊柱轴。候选轴的适应度通过建议的问题特定适应度函数进行度量。为了探索问题搜索空间，将常规遗传算子和新颖的能量最小化方法相结合应用于每个人口。

结果：结果表明，即使存在严重的形态缺陷，所提出的算法通常也能够将脊椎骨与其他骨区分开。

结论：观察到，所提出的方法是有前途的，并且在大多数样本中，所提出的算法所识别的刺与专家绘制的刺紧密匹配。专门针对脊柱裂病例的计算机辅助超声诊断系统尚不存在，但是识别脊柱的算法（例如本工作中提出的算法）是朝诊断系统迈出的第一步。将来，我们打算通过改进分割阶段并进一步优化遗传算法的各个阶段来改进算法。