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作 者:丁红[1] 张永[2] 王蕴慧[1] 王振花[1] 罗葆明
机构地区:[1]中山大学孙逸仙纪念医院围产专科,广州510120 [2]中山大学信息学院 [3]超声科
出 处:《中华超声影像学杂志》2013年第11期977-980,共4页Chinese Journal of Ultrasonography
基 金:广东省科技计划项目(20108031400001);广东省人口和计划生育委员会科研项目(20110319)
摘 要:目的利用计算机图像识别技术建立胎儿颈项透明层(NT)超声图像质量评估的模型及软件原型。方法将待测图像划分为4个待测的子图像块-鼻骨、NT、中脑、下颌骨和前胸区域。采用Gabor特征描述和贝叶斯决策判别的图像匹配算法,将输入图像的4个子图像块与标准训练集图像块的对比判定结果作为对输入图像的质量评价。结果胎儿NT超声图像的自动评估与专家人工评估的一致性较高,Kappa系数为0.795,P〈0.001。结论图像识别技术能有效地辅助超声医师对胎儿NT超声图像的质量进行快速评估,该方法能减少人工评估的主观性,提高超声筛查的准确性。Objective To establish the model and software for quality assessment of fetal nuchal translucency ultrasound image using computer image recognition technology. Methods The proposed approach firstly divided the input image into four sub-image blocks: the nasal bone(NB) area, the nuchal translucency (NT)area, the midbrain area, and the jaw and chest area. For each sub-image block, the algorithm compared the image block with the corresponding area of the standard training image set, and then determined whether the current image block was the qualified one using the the Gabor feature and Bayesian decision. The input ultrasound image was determined to be qualified only if it had four qualified sub-image blocks. Results The difference between our automatic method and the manual screening by experts wasting small,the method obtained Kappa = 0. 795 and P d0. 001. Moreover,the efficiency of our method was much higher than the manual screening method. Conclusions Image recognition technology can effectively assist the sonographer to assess the quality of fetal NT of ultrasound image. The proposed approach can reduce the subjectivity and randomness of the manual evaluation of NT image.
分 类 号:R445.1[医药卫生—影像医学与核医学] R714.5[医药卫生—诊断学]
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