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计算机辅助定量评价肌肉急性挫伤后高频超声二维图像纹理特征变化
赵佳琦1*,贾兰婷1,徐琪2,潘倩1,章建全1
0
(1. 海军军医大学(第二军医大学)长征医院超声诊疗科, 上海 200003;
2. 上海海事大学信息工程学院计算机科学系, 上海 201306
*通信作者)
摘要:
目的 采用超声回波强度界面多级分解法定量评价急性钝挫伤后人体肌肉高频超声二维图像纹理特征的变化,初步探讨其临床应用价值。方法 采用高频超声检测10例男性上臂肌肉单纯急性挫伤患者的局部肌肉二维超声图像,于脱机状态下通过Matlab 7.0软件选取患者同一图像上的肌纹理正常感兴趣区(ROI)和肌纹理疑似损伤ROI,提取两个ROI的纹理灰度值的均值(Mean)、灰度值的标准差(SDev)、纹理的密致性(NOB)、纹理基元形状的不规则度(IRGL)、纹理基元的平均大小(SOB)、纹理分布的均匀性(HOD)、纹理分布的方向性(DOD)和纹理分布的周期性(POD)8个特征参数,采用超声回波强度界面多级分解法自动计算两个ROI之间8个纹理特征的相似度差值。选取10名男性健康志愿者同部位正常肌肉二维超声图像作为对照,任意选取两个ROI,计算两个ROI之间上述8种纹理特征的相似度差值。对上臂肌肉挫伤患者和健康志愿者8个纹理特征的相似度差值进行对比分析。结果 急性上臂肌肉挫伤区局部肌束回声增强,肌纤维层次紊乱,纹理模糊,回声变化较周边肌纹理正常区显著。急性上臂肌肉挫伤患者肌纹理疑似损伤ROI和肌纹理正常ROI之间IRGL、DOD、POD、Mean和SDev等5个纹理特征相似度差值与健康志愿者任意两个ROI之间该5个纹理特征相似度差值差异有统计学意义(P均<0.01)。结论 基于超声回波强度界面多级分解法的计算机辅助定量评价技术能够对急性挫伤后肌肉高频超声二维图像纹理特征变化做出较人眼识别更精细的量化诊断,可能具备一定的临床实用价值。
关键词:    挫伤  超声检查  计算机辅助诊断  纹理  定量
DOI:10.16781/j.0258-879x.2020.01.0006
投稿时间:2019-10-11修订日期:2019-11-06
基金项目:国家自然科学基金青年科学基金(81501492).
Computer-aided quantitative evaluation of texture features extracted from two-dimensional high frequency ultrasonograms after acute muscle contusion
ZHAO Jia-qi1*,JIA Lan-ting1,XU Qi2,PAN Qian1,ZHANG Jian-quan1
(1. Department of Ultrasound, Changzheng Hospital, Naval Medical University(Second Military Medical University), Shanghai 200003, China;
2. Department of Computer Science, Institute of Information Engineering, Shanghai Maritime University, Shanghai 201306, China
*Corresponding author)
Abstract:
Objective To quantitatively evaluate the changes of texture features extracted from two-dimensional high frequency ultrasonograms of human muscle injured by acute contusion using the multiscale decomposition of echo intensity of interface reflections, and to preliminarily explore its clinical value. Methods Two-dimensional ultrasound images of local muscles of 10 male patients with acute upper limb muscle contusion were obtained using high-frequency ultrasound. The region of interest (ROI) of normal muscle texture and the ROI of muscle texture with suspected injury on the same image of the patients were selected by Matlab 7.0 software in offline state. Eight texture parameters including mean of gray scale (Mean), standard variance of gray scale (SDev), number of blobs (NOB) of texture density, irregularity (IRGL) of texture primitive shape, mean size of blobs (SOB) of texture primitive, homogeneity of distribution (HOD) of texture uniformity, directionality of texture distribution (DOD) and periodicity of texture distribution (POD) of the two ROIs were extracted. The similarity difference values of the eight texture parameters between the two ROIs were automatically calculated by the multiscale decomposition of echo intensity of interface reflections. Two-dimensional ultrasound images of normal muscles in the same part of 10 healthy male volunteers were selected as controls, and two ROIs were randomly selected to calculate the similarity difference values of the above eight texture features between them. The similarity difference values of the eight texture features between patients with upper limb muscle contusion and healthy volunteers were compared. Results Local hyperechoic lesions were found with disordered muscle fibers and fuzzy textures in the patients with acute upper extremity muscle contusion. There were significant differences in the similarity difference of five textural parameters (IRGL, DOD, POD, Mean and SDev) between patients with acute upper limb muscle contusion and healthy controls (P<0.01). Conclusion Computer-aided quantitative evaluation based on multiscale decomposition of echo intensity of interface reflections can lead to more accurate and detailed quantitative diagnosis of texture features extracted from two-dimensional high frequency ultrasonic images of muscle injured by acute contusion than human eyes, and it may have clinical values.
Key words:  muscles  contusions  ultrasonography  computer-aided diagnosis  texture  quantitation