CN110664405B - 基于焦点质量度量估计微波乳房成像平均介电特性的方法 - Google Patents

基于焦点质量度量估计微波乳房成像平均介电特性的方法 Download PDF

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CN110664405B
CN110664405B CN201910925189.8A CN201910925189A CN110664405B CN 110664405 B CN110664405 B CN 110664405B CN 201910925189 A CN201910925189 A CN 201910925189A CN 110664405 B CN110664405 B CN 110664405B
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刘雨
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Abstract

本发明涉及一种基于焦点质量度量估计微波乳房成像的平均介电特性的方法,包括下列步骤:将乳房MRI源图进行拉伸,对源图乳房各组织进行离散化,并以乳房边界轮廓为基准,加入一层皮肤,截取一侧乳房作为乳房仿真模型;在乳房仿真模型中设置肿瘤位置和肿瘤半径,对各组织进行电磁参数赋值,在皮肤表面设天线阵列,以点源代替,每一个天线依次发射信号,其他天线接受信号,将所有的接收信号利用共焦算法进行成像处理,设置不同的介电常数值,得到对应的多张共焦图像;基于梯度的焦点质量度量;基于离散小波变换的焦点质量度量;图像信杂比SCR;根据共焦图像,得到此乳房仿真模型的平均介电特性。

Description

基于焦点质量度量估计微波乳房成像平均介电特性的方法
技术领域
本发明属于生物医学检测技术领域,涉及一种基于焦点质量度量估计微波乳房成像的平均介电特性的方法。
背景技术
乳腺肿瘤是女性发病率最高的恶性肿瘤疾病,死亡率居妇女恶性肿瘤死亡率之首。早期乳腺肿瘤的诊断无疑对提高乳腺病的治疗率以及患者的远期成活率都具有决定性的意义。目前常用的早期乳腺癌的检测方法包括乳腺X线摄影术、超声波影像技术、计算机断层扫描、核磁共振成像技术、热成像检测等,但诸多方法均存在一定的缺点,如对人体产生辐射伤害、成像对比度低、费用较高等。超宽带电磁波检测乳腺癌的原理在于不同生物组织对电磁波的吸收、反射及透射特性不同,使得天线发射的脉冲信号在乳腺组织中传播时所产生的电磁场能够反映恶性组织的丰富信息。共焦微波成像检测乳腺癌依赖于对患者特定乳腺的平均介电特性的准确了解。准确估计平均介电特性后,微波信号在肿瘤部位发生相干叠加,产生清晰的微波图像。相反,如果平均介电特性估计不准确,则会重建模糊、未聚焦的图像,可能会掩盖癌性病变。
焦点质量度量(Focal Quality Metrics,FQMs)是一种算法,用于估计整个图像的聚焦度。一直被用于在显微镜和照相机系统中,预先不知道被成像物体的位置或纹理,寻找最佳聚焦的图像。
发明内容
本发明的目的是提供一种基于焦点质量度量估计微波乳房成像的平均介电特性的方法。本发明的技术方案如下:
一种基于焦点质量度量估计微波乳房成像的平均介电特性的方法,包括下列步骤:
(1)将乳房MRI源图进行拉伸,对源图乳房各组织进行离散化,并以乳房边界轮廓为基准,加入一层皮肤,截取一侧乳房作为乳房仿真模型;
(2)在乳房仿真模型中设置肿瘤位置和肿瘤半径,对各组织进行电磁参数赋值,在皮肤表面设天线阵列,以点源代替,每一个天线依次发射信号,其他天线接受信号,将所有的接收信号利用共焦算法进行成像处理,设置不同的介电常数值,得到对应的多张共焦图像;
(3)基于梯度的焦点质量度量ΦG
Figure BDA0002218723950000021
X和Y是图像的尺寸,ID(x,y)是像素f(x,y)的八邻域灰度梯度;
(4)基于离散小波变换的焦点质量度量ΦW
Figure BDA0002218723950000022
ILH,IHL和IHH是第一级细节子带;
(5)图像信杂比SCR
Figure BDA0002218723950000023
αT是目标区域能量最大值,αB是除目标区域外的能量最大值;
(6)根据步骤(2)得到的共焦图像,计算每张图像对应的ΦG、ΦW和SCR,得到介电常数εr与ΦG、ΦW和SCR的关系曲线,并进行归一化处理;
(7)根据归一化处理后的曲线,得到当信杂比SCR=1时的介电常数值εr1,在5≤εr1≤εr1+3的范围内分别选取ΦG和ΦW的最小值对应的εrG和εrW;若
Figure BDA0002218723950000024
则此乳房仿真模型的平均介电特性为εr=εrG;若
Figure BDA0002218723950000025
则此乳房仿真模型的平均介电特性为εr=εrW
(8)选择步骤(7)确定的介电常数进行肿瘤成像,肿瘤成像位置与预设肿瘤位置的相似,则说明此乳房模型的平均介电常数为由步骤(7)确定的介电常数值。
本发明比较了两种常用的焦点质量度量指标和图像信杂比(Signal-to-ClutterRatio,SCR),来精确估计微波乳房成像的平均介电特性。
附图说明
图1乳房MRI源图
图2乳房模型肿瘤位置和天线位置图
图3介电常数εr与ΦG、ΦW和SCR的关系曲线
图4εr=6.9对应的肿瘤成像图
具体实施方式
下面结合附图和实例对本发明进行说明。
(1)图1为乳房MRI源图,首先将图片进行一次拉伸处理,将其拉伸为600×600像素点,使图片中的每一个像素点对应一个FDTD网格,该步骤在MATLAB中进行,首先读入仅包含图片本身的源图,将其转化为灰度值矩阵,再利用imresize命令对图片拉伸,对源图乳房各组织进行离散化,并以乳房边界轮廓为基准,加入一层皮肤,通常只考虑一侧乳房,截取右乳房作为仿真模型
(2)在乳房中设置肿瘤位置(40,40)和肿瘤半径3mm,对各组织进行电磁参数赋值,在皮肤表面布放天线阵列,以点源代替(如图2所示),每一个天线依次发射信号,其他天线接受信号,将所有的接收信号利用共焦算法进行成像处理,设置介电常数值范围为5≤εr≤23,采样间隔为0.1,得到对应的181张共焦图像;
(3)根据步骤(2)得到的共焦图像,计算每张图像对应的ΦG、ΦW和SCR,得到介电常数εr与ΦG、ΦW和SCR的关系曲线,并进行归一化处理(如图3所示);
(4)观察图3,得到当信杂比SCR=1时的介电常数值εr1=6.电,在5≤εr1≤9.电的范围内分别选取ΦG和ΦW的最小值对应的εrG=6.9和εrW=7.0,其对应的SCR值分别为
Figure BDA0002218723950000031
Figure BDA0002218723950000032
显然
Figure BDA0002218723950000033
则此乳房模型的平均介电特性为εr=εrG=6.9。
(5)选择εr=6.9,用共焦成像算法对肿瘤进行成像,肿瘤的成像位置为(40,39)(如图4所示),与预设肿瘤位置相似,所以此乳房模型的平均介电常数为6.9。

Claims (1)

1.一种基于焦点质量度量估计微波乳房成像的平均介电特性的方法,包括下列步骤:
(1)将乳房MRI源图进行拉伸,对源图乳房各组织进行离散化,并以乳房边界轮廓为基准,加入一层皮肤,截取一侧乳房作为乳房仿真模型;
(2)在乳房仿真模型中设置肿瘤位置和肿瘤半径,对各组织进行电磁参数赋值,在皮肤表面设天线阵列,以点源代替,每一个天线依次发射信号,其他天线接受信号,将所有的接收信号利用共焦算法进行成像处理,设置不同的介电常数值,得到对应的多张共焦图像;
(3)基于梯度的焦点质量度量ΦG
Figure FDA0002218723940000011
X和Y是图像的尺寸,ID(x,y)是像素f(x,y)的八邻域灰度梯度;
(4)基于离散小波变换的焦点质量度量ΦW
Figure FDA0002218723940000012
ILH,IHL和IHH是第一级细节子带;
(5)图像信杂比SCR
Figure FDA0002218723940000013
αT是目标区域能量最大值,αB是除目标区域外的能量最大值;
(6)根据步骤(2)得到的共焦图像,计算每张图像对应的ΦG、ΦW和SCR,得到介电常数εr与ΦG、ΦW和SCR的关系曲线,并进行归一化处理;
(7)根据归一化处理后的曲线,得到当信杂比SCR=1时的介电常数值εr1,在5≤εr1≤εr1+3的范围内分别选取ΦG和ΦW的最小值对应的εrG和εrW;若
Figure FDA0002218723940000014
则此乳房仿真模型的平均介电特性为εr=εrG;若
Figure FDA0002218723940000015
则此乳房仿真模型的平均介电特性为εr=εrW
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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1623506A (zh) * 2003-12-07 2005-06-08 倪蔚民 基于虹膜纹理分析的生物测定系统
CN105376469A (zh) * 2014-11-03 2016-03-02 倪蔚民 一种用于生物特征识别移动终端的驱动自动聚焦方法
CN107212884A (zh) * 2017-05-11 2017-09-29 天津大学 一种仰卧体位压迫乳房成像方法

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* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US7454242B2 (en) * 2003-09-17 2008-11-18 Elise Fear Tissue sensing adaptive radar imaging for breast tumor detection
US20090238426A1 (en) * 2008-03-19 2009-09-24 Uti Limited Partnership System and Methods for Identifying an Object within a Complex Environment

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN1623506A (zh) * 2003-12-07 2005-06-08 倪蔚民 基于虹膜纹理分析的生物测定系统
CN105376469A (zh) * 2014-11-03 2016-03-02 倪蔚民 一种用于生物特征识别移动终端的驱动自动聚焦方法
CN107212884A (zh) * 2017-05-11 2017-09-29 天津大学 一种仰卧体位压迫乳房成像方法

Non-Patent Citations (3)

* Cited by examiner, † Cited by third party
Title
Focal quality metrics for the objective evaluation of confocal microwave images;Anja Skrivervik等;《International Journal of Microwave and Wireless Technologies》;20170627;第9卷(第7期);全文 *
Parameter Search Algorithms for Microwave Radar-Based Breast Imaging: Focal Quality Metrics as Fitness Functions;Declan O’Loughlin等;《Sensors》;20171206;第17卷(第12期);全文 *
微波检测乳腺肿瘤的成像与快速识别;王梁;《中国优秀博硕士学位论文全文数据库(博士)医药卫生科技辑》;20180915(第09期);全文 *

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