CN105686844A - 前a%区域作参考区的人脑局部水分布容积测定方法 - Google Patents

前a%区域作参考区的人脑局部水分布容积测定方法 Download PDF

Info

Publication number
CN105686844A
CN105686844A CN201510998487.1A CN201510998487A CN105686844A CN 105686844 A CN105686844 A CN 105686844A CN 201510998487 A CN201510998487 A CN 201510998487A CN 105686844 A CN105686844 A CN 105686844A
Authority
CN
China
Prior art keywords
water distribution
human brain
distribution volume
district
region
Prior art date
Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
Granted
Application number
CN201510998487.1A
Other languages
English (en)
Other versions
CN105686844B (zh
Inventor
吴义根
郑改革
赵德林
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Yiyi International Medical Technology Beijing Co ltd
Original Assignee
Nanjing University of Information Science and Technology
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Nanjing University of Information Science and Technology filed Critical Nanjing University of Information Science and Technology
Priority to CN201510998487.1A priority Critical patent/CN105686844B/zh
Publication of CN105686844A publication Critical patent/CN105686844A/zh
Application granted granted Critical
Publication of CN105686844B publication Critical patent/CN105686844B/zh
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

Classifications

    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/02Arrangements for diagnosis sequentially in different planes; Stereoscopic radiation diagnosis
    • A61B6/03Computed tomography [CT]
    • A61B6/037Emission tomography
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/46Arrangements for interfacing with the operator or the patient
    • A61B6/467Arrangements for interfacing with the operator or the patient characterised by special input means
    • A61B6/469Arrangements for interfacing with the operator or the patient characterised by special input means for selecting a region of interest [ROI]
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/48Diagnostic techniques
    • A61B6/481Diagnostic techniques involving the use of contrast agents
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/50Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body parts; specially adapted for specific clinical applications
    • A61B6/501Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment specially adapted for specific body parts; specially adapted for specific clinical applications for diagnosis of the head, e.g. neuroimaging or craniography
    • AHUMAN NECESSITIES
    • A61MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61BDIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B6/00Apparatus or devices for radiation diagnosis; Apparatus or devices for radiation diagnosis combined with radiation therapy equipment
    • A61B6/52Devices using data or image processing specially adapted for radiation diagnosis

Landscapes

  • Health & Medical Sciences (AREA)
  • Life Sciences & Earth Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Medical Informatics (AREA)
  • Biomedical Technology (AREA)
  • Surgery (AREA)
  • High Energy & Nuclear Physics (AREA)
  • Physics & Mathematics (AREA)
  • Nuclear Medicine, Radiotherapy & Molecular Imaging (AREA)
  • Optics & Photonics (AREA)
  • Pathology (AREA)
  • Radiology & Medical Imaging (AREA)
  • Veterinary Medicine (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Molecular Biology (AREA)
  • Biophysics (AREA)
  • Animal Behavior & Ethology (AREA)
  • General Health & Medical Sciences (AREA)
  • Public Health (AREA)
  • Computer Vision & Pattern Recognition (AREA)
  • Human Computer Interaction (AREA)
  • Neurology (AREA)
  • Neurosurgery (AREA)
  • Dentistry (AREA)
  • Oral & Maxillofacial Surgery (AREA)
  • Investigating Or Analysing Biological Materials (AREA)
  • Nuclear Medicine (AREA)

Abstract

本发明公开了一种前A%区域作参考区的人脑局部水分布容积测定方法,其特征在于,包括如下步骤:步骤一:对人脑做PET/H2 15O动态扫描;步骤二:将人脑的前A%区域作为参考区,计算出人脑中每个待求部位的相对水分布容积值P1;步骤三:求出人脑每个部位的相对水分布容积值P1后,根据需要作人脑的归一化处理;所得数值与该部位的绝对水分布容积仅相差一比例常数,用该所得数值作为绝对水分布容积的指标。本发明既不需要动态抽取动脉血也不需要可能失真的模版或模型,更不需要做复杂的修正等人工干预,因而便于实现计算机的自动化处理。同时测定的结果与精确局部水分布容积定量测定方法没有偏差,具有很好的应用情景。

Description

前A%区域作参考区的人脑局部水分布容积测定方法
技术领域
本发明涉及一种人脑局部水分布容积测定方法,具体涉及一种前A%区域作参考区的人脑局部水分布容积测定方法。本发明属于生物及医学成像领域。
背景技术
利用正电子放射性核素15O标记的水(即H2 15O)作显像剂的正电子发射断层显像(PositronEmissionTomography,即PET)方法(简记为PET/H2 15O方法),是对静脉注射H215O后进行PET动态扫描,而后用Kety-Schmidt单室模型(文献见KetySS.(1951)Thetheoryandapplicationsoftheexchangeofinertgasatthelungsandtissues.PharmacolRev3:1-41.)等方法作局部水分布容积逐像素定量计算,这样可以生成局部水分布容积的图像。
早期的定量计算中输入函数需要通过动态抽取动脉血或者动脉化的静脉血的方法来测得。尽管这种方法很准确和有效,但它是有损伤的,因此这种方法日常很少应用。为了减少或者消除这种抽血方法的影响,一些研究者发明了一种称为源自图像的(image-derived)的方法(包括两份文献,文献1见WeinbergI,HuangSC,HoffmanE,etal.(1988)ValidationofPET-acquiredinputfunctionsforcardiacstudies.JNuclMed29:241-247,文献2见ChenK,BandyD,ReimanE,etal.(1998)NoninvasiveQuantificationoftheCerebralMetabolicRateforGlucoseUsingPositronEmissionTomography,18F-Fluoro-2-Deoxyglucose,thePatlakMethod,andanImage-DerivedInputFunction.JCerebBloodFlowMetab18:716–723)。将PET图像中主要反映血浆特性的动脉血管或左心室的PET数据作为输入函数。这些方法虽然成功地用来代替动态抽血,但不准确或者需要许多复杂的手工修正。有鉴于此,一种从一群人血样数据中计算出的输入函数模板或对此血样数据进行拟合给出的输入函数解析模型(文献见FengD,HuangSC,WangX(1993)Modelsforcomputersimulationstudiesofinputfunctionsfortracerkineticmodelingwithpositronemissiontomography.IntJBiomedComput32:95-110.)被引进,但这些模版或模型不能很好地符合个别被试的特殊血样数据,这样的输入函数无法简单应用于水分布容积的定量计算。
正如前述,现有技术存在下述问题:
1)通过动态抽取动脉血或者动脉化的静脉血获取输入函数的方法,尽管很准确和有效,但它是有损伤的,容易带来不舒适,甚至会引起血管方面的其他危险,并有血样放射物处理以及对人的干扰等麻烦,因此这种方法日常很少应用。
2)源自图像的(image-derived)的方法,存在这样的问题:a)需要快速的图像采集方案来反映输入函数的时间曲线特征,特别是注射FDG后早期的迅速变化;b)需要有效解决局部体积效应;c)需要修正从围绕所选ROI的脑区到这些ROI的外流效应(spillover)。当示踪剂在围绕所选ROI的脑区中开始积聚时,这种组织到血浆的外流将变得很严重。因而这些方法虽然成功地用来代替动态抽血,但不准确或者需要许多复杂的手工修正。
3)对于输入函数模版或模型方法,由于每个个体的特殊血样数据不一定具有相同的特定值,如果统一选用这样的模版或模型将导致给出的输入函数失真,无法简单应用于水分布容积的定量计算。
发明内容
为解决现有技术的不足,本发明的目的在于提供一种前A%区域作参考区的人脑局部水分布容积测定方法,以解决现有技术在测定人脑局部水分布容积时准确性不足的技术问题。
为了实现上述目标,本发明采用如下的技术方案:
前A%区域作参考区的人脑局部水分布容积测定方法,其特征在于,包括如下步骤:
步骤一:对人脑做PET/H2 15O动态扫描;
步骤二:将人脑的前A%区域作为参考区,计算出人脑中每个待求部位的相对水分布容积值P1,所述前A%区域指将人大脑的全部像素的H2 15O放射性活度值从大到小进行排序后得到的活度值排在前A%的所有像素的集合,A%为一个比例值;
步骤三:求出人脑每个部位的相对水分布容积值P1后,根据需要作人脑的归一化处理;所得数值与该部位的绝对水分布容积仅相差一比例常数,用该所得数值作为绝对水分布容积的指标。
前述的前A%区域作参考区的人脑局部水分布容积测定方法,其特征在于,所述的PET/H2 15O动态扫描为用H2 15O作显像剂的PET动态扫描方法。
前述的前A%区域作参考区的人脑局部水分布容积测定方法,其特征在于,步骤二中,采用公式: ∫ 0 t C t o ( τ ) d τ = P 1 ∫ 0 t C t r ( τ ) d τ + P 2 C t r ( t ) - P 3 C t o ( t ) , 计算人脑中每个待求部位的相对水分布容积值P1;其中:cto(t)为t时刻待求部位的单位体积的H2 15O放射性活度,ctr(t)为t时刻前A%区域的单位体积的H215O放射性活度,P2、P3是其它两个拟合参数;通过动态测量采样,拟合得到P1、P2、P3
前述的前A%区域作参考区的人脑局部水分布容积测定方法,其特征在于,步骤三中,在需要测定绝对水分布容积值时,将测定出的相对水分布容积值P1乘以前A%区域的绝对水分布容积值即可。
前述的前A%区域作参考区的人脑局部水分布容积测定方法,其特征在于,可以基于像素进行定量测定。
前述的前A%区域作参考区的人脑局部水分布容积测定方法,其特征在于,归一化后的图像至少能够用于单个人体不同状态或不同人体间的比较研究。
前述的前A%区域作参考区的人脑局部水分布容积测定方法,其特征在于,所述8<A<20。
前述的前A%区域作参考区的人脑局部水分布容积测定方法,其特征在于,A=10。
本发明的有益之处在于:本发明可以对所分析的器官逐像素进行局部水分布容积的定量测定,进而生成人脑局部水分布容积的功能图像,无需输入函数,从而既不需要动态抽取动脉血也不需要可能失真的模版或模型,更不需要做复杂的修正等人工干预,因而便于实现计算机的自动化处理。同时测定的结果与精确局部水分布容积定量测定方法没有偏差,这种完全无损伤的定量测定方法具有很好的应用情景。
附图说明
图1是本发明前A%区域作参考区的人脑局部水分布容积测定方法的流程示意图;
图2是噪声水平为1的情况下本发明与Kety-Schmidt单室模型方法测定的相对水分布容积的回归比较示意图;
图3是是噪声水平为1的情况下本发明与Kety-Schmidt单室模型方法测定的绝对水分布容积的回归比较示意图。
具体实施方式
以下结合附图和具体实施例对本发明作具体的介绍。
参照图1所示,本发明前A%区域作参考区的人脑局部水分布容积测定方法,为一种人脑局部水分布容积的PET/H2 15O无损伤定量测定方法,该方法可以对人脑逐像素进行定量测定,进而生成人脑局部水分布容积局的功能图像。为实现上述发明目的,本发明是采取以下的技术方案来实现的:
前A%区域作参考区的人脑局部水分布容积定量测定方法,其特征在于:
(1)对人脑做PET/H2 15O动态扫描;PET/H2 15O动态扫描为用H2 15O作显像剂的PET动态扫描方法;
(2)将人大脑的全部像素的H2 15O放射性活度值从大到小进行排序,取活度值排在前A%的所有像素的集合作为参考区(简称前A%区域),这里的A%为一个百分比值,其小于100%。然后直接采用下列公式:
&Integral; 0 t C t o ( &tau; ) d &tau; = P 1 &Integral; 0 t C t r ( &tau; ) d &tau; + P 2 C t r ( t ) - P 3 C t o ( t ) 计算出人脑中每个待求部位的相对水分布容积值P1,式中cto(t)为t时刻待求部位的单位体积的H2 15O放射性活度,ctr(t)为t时刻前A%区域的单位体积的H2 15O放射性活度,P2、P3是其它两个拟合参数;通过动态测量采样,拟合得到P1、P2、P3
(3)当求出人脑每个部位的相对水分布容积值P1后,根据需要可作人脑的归一化处理。所得数值与该部位的绝对水分布容积仅相差一比例常数,可以用它作绝对水分布容积的指标。这个归一化后的图像可以用于单个人体不同状态或不同人体间的比较研究等。
需要指出的是,本发明中A的取值不应该过大或者过小,如果A取值过大,会造成与金标准Kety-Schmidt单室模型方法的偏差,如果A的取值过小,会使拟合参数的误差变大,作为优选,A的取值应该是8<A<20。在这个区间内,能够较好实现相对水分布容积值的测定。如需要测定绝对水分布容积值,优选建议A取为10,此种情况下,前10%区域的绝对水分布容积值已经为现有的文献资料公开,将测定出的相对水分布容积值P1乘以前10%区域的绝对水分布容积值即得。当A不取10时,比如取12,此时前A%区域的绝对水分布容积值需要根据实验取得,本领域技术人员可以根据现有技术,仿照取得前10%区域的绝对水分布容积值的方式,取得前A%区域的绝对水分布容积值。本发明方法测定的绝对水分布容积值全域分布的特征与真实情况相比没有偏差。本发明可以基于像素进行定量测定。
下面再结合图2、图3介绍用模拟数据(根据已有文献报道的实验数据参数用计算机随机产生的PET/H215O动态扫描数据)进行的本发明与国际公认的金标准Kety-Schmidt单室模型方法测定结果的比较:
图2、图3分别是选用前10%区域作参考区(绝对血流值取为1.0毫升/毫升/分钟,绝对水分布容积值取0.86毫升/毫升,此值取之于已有文献报道的实验结果,且此值为文献中已有实验所有被测者的平均值。当A的取值为10时,能够最佳实现本发明技术效果,本领域技术人员在A的取值不为10时,相对水分布容积值的计算可以实现。)在噪声水平为1的情况下大脑逐像素本发明与Kety-Schmidt单室模型方法两种测定出的相对(图1)和绝对(图2)水分布容积值的回归比较。图中散点对应每个像素的结果,直线为两种方法的回归直线,其斜率都为1.01,很接近于1;截距为0.000。这表明本发明的结果与Kety-Schmidt单室模型方法几乎是成正比的,因而二者相等价。这些结果显示本发明和Kety-Schmidt单室模型方法的计算结果近似,但不像传统的方法那样需要输入函数,从而免去了前述背景技术中所描述的那些困惑。
由上所述可见,本发明选用前A%区域作参考区后,直接利用前述的无损伤局部水分布容积定量计算公式,输入函数将消失。当需要测定绝对水分布容积时,将测定出的相对水分布容积值乘以前A%区域的绝对水分布容积值即可。这样计算出每个像素或区域的绝对水分布容积值与真值相比仅相差一小的比例常数,,甚至计算出每个像素或区域的绝对水分布容积值与真值相等。也就是所计算出绝对水分布容积值的全域分布特征与真实情况相比不会出现偏差。
由于本发明方法不像源自图像方法那样需要复杂的修正,且不需要输入函数,从而既不需要动态抽取动脉血也不需要做复杂的修正等人工干预,因而便于实现计算机的自动化处理。同时我们的结果与精确局部水分布容积定量测定方法没有偏差,本发明有望应用于日常需要。
以上显示和描述了本发明的基本原理、主要特征和优点。本行业的技术人员应该了解,上述实施例不以任何形式限制本发明,凡采用等同替换或等效变换的方式所获得的技术方案,均落在本发明的保护范围内。

Claims (8)

1.前A%区域作参考区的人脑局部水分布容积测定方法,其特征在于,包括如下步骤:
步骤一:对人脑做PET/H2 15O动态扫描;
步骤二:将人脑的前A%区域作为参考区,计算出人脑中每个待求部位的相对水分布容积值P1,所述前A%区域指将人大脑的全部像素的H2 15O放射性活度值从大到小进行排序后得到的活度值排在前A%的所有像素的集合;
步骤三:求出人脑每个部位的相对水分布容积值P1后,根据需要作人脑的归一化处理;所得数值与该部位的绝对水分布容积仅相差一比例常数,用该所得数值作为绝对水分布容积的指标。
2.根据权利要求1所述的前A%区域作参考区的人脑局部水分布容积测定方法,其特征在于,所述的PET/H2 15O动态扫描为用H2 15O作显像剂的PET动态扫描方法。
3.根据权利要求2所述的前A%区域作参考区的人脑局部水分布容积测定方法,其特征在于,步骤二中,采用公式:
&Integral; 0 t C t o ( &tau; ) d &tau; = P 1 &Integral; 0 t C t r ( &tau; ) d &tau; + P 2 C t r ( t ) - P 3 C t o ( t ) , 计算人脑中每个待求部位的相对水分布容积值P1;其中:cto(t)为t时刻待求部位的单位体积的H2 15O放射性活度,ctr(t)为t时刻前A%区域的单位体积的H2 15O放射性活度,P2、P3是其它两个拟合参数;通过动态测量采样,拟合得到P1、P2、P3
4.根据权利要求3所述的前A%区域作参考区的人脑局部水分布容积测定方法,其特征在于,步骤三中,在需要测定绝对水分布容积值时,将测定出的相对水分布容积值P1乘以前A%区域的绝对水分布容积值即可。
5.根据权利要求4所述的前A%区域作参考区的人脑局部水分布容积测定方法,其特征在于,可以基于像素进行定量测定。
6.根据权利要求5所述的前A%区域作参考区的人脑局部水分布容积测定方法,其特征在于,归一化后的图像至少能够用于单个人体不同状态或不同人体间的比较研究。
7.根据权利要求1至6任一项所述的前A%区域作参考区的人脑局部水分布容积测定方法,其特征在于,所述8<A<20。
8.根据权利要求7所述的前A%区域作参考区的人脑局部水分布容积测定方法,其特征在于,A=10。
CN201510998487.1A 2015-12-28 2015-12-28 前a%区域作参考区的人脑局部水分布容积测定方法 Active CN105686844B (zh)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201510998487.1A CN105686844B (zh) 2015-12-28 2015-12-28 前a%区域作参考区的人脑局部水分布容积测定方法

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201510998487.1A CN105686844B (zh) 2015-12-28 2015-12-28 前a%区域作参考区的人脑局部水分布容积测定方法

Publications (2)

Publication Number Publication Date
CN105686844A true CN105686844A (zh) 2016-06-22
CN105686844B CN105686844B (zh) 2018-11-16

Family

ID=56225899

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201510998487.1A Active CN105686844B (zh) 2015-12-28 2015-12-28 前a%区域作参考区的人脑局部水分布容积测定方法

Country Status (1)

Country Link
CN (1) CN105686844B (zh)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105997120A (zh) * 2015-12-28 2016-10-12 南京信息工程大学 前a%区域作参考区的人脑局部水分布容积测定方法

Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101172038A (zh) * 2007-09-27 2008-05-07 南京信息工程大学 用于人脑等器官局部葡萄糖代谢率的无损伤定量计算方法
CN101320468A (zh) * 2007-06-07 2008-12-10 株式会社东芝 数据处理装置、医用诊断装置、数据处理方法以及医用诊断方法
CN102068269A (zh) * 2011-01-21 2011-05-25 南京信息工程大学 用于人体器官局部血流的无损伤定量测定方法
US20140010430A1 (en) * 2011-02-24 2014-01-09 Dog Microsystems Inc. Method and apparatus for isolating a potential anomaly in imaging data and its application to medical imagery
US20140177934A1 (en) * 2012-06-20 2014-06-26 Toshiba Medical Systems Corporation Image diagnosis device and control method thereof

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN101320468A (zh) * 2007-06-07 2008-12-10 株式会社东芝 数据处理装置、医用诊断装置、数据处理方法以及医用诊断方法
CN101172038A (zh) * 2007-09-27 2008-05-07 南京信息工程大学 用于人脑等器官局部葡萄糖代谢率的无损伤定量计算方法
CN102068269A (zh) * 2011-01-21 2011-05-25 南京信息工程大学 用于人体器官局部血流的无损伤定量测定方法
US20140010430A1 (en) * 2011-02-24 2014-01-09 Dog Microsystems Inc. Method and apparatus for isolating a potential anomaly in imaging data and its application to medical imagery
US20140177934A1 (en) * 2012-06-20 2014-06-26 Toshiba Medical Systems Corporation Image diagnosis device and control method thereof

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
吴义根等: "脑局部葡萄糖代谢率PET/FDG定量计算的误差分析", 《自然科学进展》 *

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN105997120A (zh) * 2015-12-28 2016-10-12 南京信息工程大学 前a%区域作参考区的人脑局部水分布容积测定方法

Also Published As

Publication number Publication date
CN105686844B (zh) 2018-11-16

Similar Documents

Publication Publication Date Title
Sullivan et al. Metrology standards for quantitative imaging biomarkers
Karim et al. Evaluation of state-of-the-art segmentation algorithms for left ventricle infarct from late Gadolinium enhancement MR images
Peng et al. Normal values of myocardial deformation assessed by cardiovascular magnetic resonance feature tracking in a healthy Chinese population: a multicenter study
Huo et al. Fully automatic liver attenuation estimation combing CNN segmentation and morphological operations
CN107945878A (zh) 一种基于放射组学的肝静脉压力梯度计算模型的构建方法
CN102068269B (zh) 用于人体器官局部血流的无损伤定量测定方法
Cau et al. Potential role of artificial intelligence in cardiac magnetic resonance imaging: can it help clinicians in making a diagnosis?
US20210391078A1 (en) Deep learning model learning device and method for cancer region
Carminati et al. Comparison of image processing techniques for nonviable tissue quantification in late gadolinium enhancement cardiac magnetic resonance images
Piper et al. Objective evaluation of the correction by non-rigid registration of abdominal organ motion in low-dose 4D dynamic contrast-enhanced CT
Khan et al. A novel system for scoring of hormone receptors in breast cancer histopathology slides
CN100569183C (zh) 用于人体器官局部葡萄糖代谢率的无损伤定量计算方法
O'Brien et al. Automated left ventricle ischemic scar detection in CT using deep neural networks
Qian et al. Segmentation of myocardium from cardiac MR images using a novel dynamic programming based segmentation method
Cavalcanti et al. Unmixing dynamic PET images with variable specific binding kinetics
Beache et al. Fully automated framework for the analysis of myocardial first‐pass perfusion MR images
US10417764B2 (en) System and methods for diagnostic image analysis and image quality assessment
Vegas-Sánchez-Ferrero et al. Statistical characterization of noise for spatial standardization of CT scans: enabling comparison with multiple kernels and doses
Corsi et al. Improved quantification of left ventricular volumes and mass based on endocardial and epicardial surface detection from cardiac MR images using level set models
Teo et al. Regional ejection fraction and regional area strain for left ventricular function assessment in male patients after first-time myocardial infarction
Buckler et al. Inter-method performance study of tumor volumetry assessment on computed tomography test-retest data
CN105686844A (zh) 前a%区域作参考区的人脑局部水分布容积测定方法
van der Zee et al. TimTrack: A drift-free algorithm for estimating geometric muscle features from ultrasound images
Gearhart et al. Artificial intelligence in echocardiography to diagnose congenital heart disease and fetal echocardiography
CN105748093A (zh) 大脑灰质作参考区的人脑局部水分布容积测定方法

Legal Events

Date Code Title Description
C06 Publication
PB01 Publication
C10 Entry into substantive examination
SE01 Entry into force of request for substantive examination
GR01 Patent grant
GR01 Patent grant
TR01 Transfer of patent right

Effective date of registration: 20210526

Address after: Room 1, B416, e-commerce main building, 2345 Chuangxin 1st Road, Songbei District, Harbin City, Heilongjiang Province

Patentee after: Harbin benhong Biotechnology Co.,Ltd.

Address before: No.219, ningliu Road, Nanjing, Jiangsu, 210016

Patentee before: Nanjing University of Information Science and Technology

TR01 Transfer of patent right
TR01 Transfer of patent right

Effective date of registration: 20230825

Address after: Room 1602, Unit 4, Building 8, No. 188 Huangyimudian Road, Chaoyang District, Beijing, 100020

Patentee after: Gao Cui

Address before: Room 1, B416, e-commerce main building, 2345 Chuangxin 1st Road, Songbei District, Harbin City, Heilongjiang Province

Patentee before: Harbin benhong Biotechnology Co.,Ltd.

TR01 Transfer of patent right
TR01 Transfer of patent right

Effective date of registration: 20231008

Address after: B201, 2nd Floor, Block B, No.13 Sixinzhuang Road, Guanzhuang Township, Chaoyang District, Beijing, 100020

Patentee after: Yiyi International Medical Technology (Beijing) Co.,Ltd.

Address before: Room 1602, Unit 4, Building 8, No. 188 Huangyimudian Road, Chaoyang District, Beijing, 100020

Patentee before: Gao Cui

TR01 Transfer of patent right
TR01 Transfer of patent right

Effective date of registration: 20240604

Address after: No. 267 Gejia Village, Wanggang Town, Linying County, Luohe City, Henan Province, 462600

Patentee after: Zhang Huichuang

Country or region after: China

Address before: B201, 2nd Floor, Block B, No.13 Sixinzhuang Road, Guanzhuang Township, Chaoyang District, Beijing, 100020

Patentee before: Yiyi International Medical Technology (Beijing) Co.,Ltd.

Country or region before: China

TR01 Transfer of patent right
TR01 Transfer of patent right

Effective date of registration: 20240611

Address after: Room 1602, Unit 4, Building 8, No. 188 Huangyimudian Road, Chaoyang District, Beijing, 100020

Patentee after: Gao Cui

Country or region after: China

Patentee after: Liu Shu

Address before: No. 267 Gejia Village, Wanggang Town, Linying County, Luohe City, Henan Province, 462600

Patentee before: Zhang Huichuang

Country or region before: China

TR01 Transfer of patent right

Effective date of registration: 20240627

Address after: B201, 2nd Floor, Block B, No.13 Sixinzhuang Road, Guanzhuang Township, Chaoyang District, Beijing, 100000

Patentee after: Yiyi International Medical Technology (Beijing) Co.,Ltd.

Country or region after: China

Address before: Room 1602, Unit 4, Building 8, No. 188 Huangyimudian Road, Chaoyang District, Beijing, 100020

Patentee before: Gao Cui

Country or region before: China

Patentee before: Liu Shu