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中文摘要
翻译
本研究的目的是探讨乳腺断层合成摄影,以提高灵敏度 和乳腺癌检测的特异性。通过去除重叠的组织,该系统可以允许 检测模糊的病变,并允许更好的病变的3D表征。 拟议研究的具体目标是: (1)使用标本和患者图像优化断层合成技术。 (2)实施断层合成图像和CAD输出的软拷贝显示系统, 放射科医生的生产力和性能。 (3)进行前瞻性初步研究,以评价放射科医师使用乳腺断层合成摄影的表现。 (4)研究乳腺肿块的CAD作为乳腺断层合成摄影的组成部分。 在初步研究中,我们评估了一个调查数字的物理特性, 乳腺X射线摄影系统修改为断层合成扫描,并优化了射线照相 断层合成技术。我们将胸部断层合成的经验转化为 乳房X线摄影,并证明了我们的重建算法的可行性, 乳房切除标本和病人我们开发了新的CAD算法检测乳房 在乳腺X射线摄影中,我们可以将这些经验转化为3D断层合成数据。 本提案提出了一个完整的计划,以证明物理和临床可行性。于 成功完成每一个目标,直接的好处将是至关重要的信息, 同时,我们的工业合作伙伴也将促进该乳腺断层合成系统的商业化, 作为对其他学术团体和制造商的类似系统的评估。
英文摘要
The purpose of this study is to investigate tomosynthesis mammography to improve the sensitivity and specificity of breast cancer detection. By removing overlapping tissue, this system can allow detection of obscured lesions and permit better 3D characterization of lesions. The specific aims of the proposed study are to: (1) Optimize tomosynthesis technique using specimen and patient images. (2) Implement soft-copy display system for tomosynthesis images and CAD outputs to maximize radiologist productivity and performance. (3) Perform prospective pilot studies to evaluate radiologist performance with breast tomosynthesis. (4) Investigate CAD of breast masses as an integral component of breast tomosynthesis. In preliminary studies, we evaluated the physical characteristics of an investigational digital mammography system modified for tomosynthesis scanning, and optimized the radiographic technique for tomosynthesis. We translated our experience with chest tomosynthesis into mammography, and demonstrated feasibility of our reconstruction algorithm on phantoms, mastectomy specimens, and patients. We developed novel CAD algorithms for the detection of breast masses in mammography, and will parlay that experience into the 3D tomosynthesis data. This proposal presents a complete plan to demonstrate physical and clinical feasibility. Upon the successful completion of each aim, the immediate benefit will be crucial information which will facilitate commercial translation of this breast tomosynthesis system by our industrial partner, as well as the evaluation of similar systems from other academic groups and manufacturers.
期刊论文(7)
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会议论文
DOI: 10.1016/j.acra.2008.09.013
发表时间: 2009
期刊: Academic radiology
影响因子: 4.8
作者: [Chawla,AmarpreetS, Saunders,RobertS, Singh,Swatee, Lo,JosephY, Samei,Ehsan]
通讯作者: Samei,Ehsan
The quantitative potential for breast tomosynthesis imaging.
乳腺断层合成成像的定量潜力。
DOI: 10.1118/1.3285038
发表时间: 2010
期刊: Medical physics
影响因子: 3.8
作者: [Shafer,ChristinaM, Samei,Ehsan, Lo,JosephY]
通讯作者: Lo,JosephY
Impulse response and Modulation Transfer Function analysis for Shift-And-Add and Back Projection image reconstruction algorithms in Digital Breast Tomosynthesis (DBT).
数字乳腺断层合成 (DBT) 中移位相加和背投影图像重建算法的脉冲响应和调制传递函数分析。
DOI: 10.1504/ijfipm.2008.020187
发表时间: 2008
期刊: International journal of functional informatics and personalised medicine
影响因子: --
作者: [Chen,Ying, Lo,JosephY, Dobbins3rd,JamesT]
通讯作者: Dobbins3rd,JamesT
Computer-Aided Triage of Body CT Scans with Deep Learning
  • 批准号:
    10585553
  • 项目类别:
  • 资助金额:
    $58.68万
  • 财政年份:
    2023
  • 负责人:
    JOSEPH Y LO
  • 依托单位:
TR&D Project 3: Virtual Readers
  • 批准号:
    10551846
  • 项目类别:
  • 资助金额:
    $31.44万
  • 财政年份:
    2021
  • 负责人:
    JOSEPH Y LO
  • 依托单位:
TR&D Project 3: Virtual Readers
  • 批准号:
    10089804
  • 项目类别:
  • 资助金额:
    $28.3万
  • 财政年份:
    2021
  • 负责人:
    JOSEPH Y LO
  • 依托单位:
TR&D Project 3: Virtual Readers
  • 批准号:
    10372911
  • 项目类别:
  • 资助金额:
    $31.44万
  • 财政年份:
    2021
  • 负责人:
    JOSEPH Y LO
  • 依托单位:
海外基金