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Elastography-based Analytics for Benign and Malignant Breast Disease

Elastography-based Analytics for Benign and Malignant Breast Disease
基于弹性成像的良性和恶性乳腺疾病分析
批准号:
9516398
负责人:
Jingfeng Jiang
金额:
$45.02万
依托单位国家:
美国
项目类别:
财政年份:
2018
资助国家:
美国
项目状态:
已结题
起止时间:
2018-08-01 至 2023-07-31

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中文摘要
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英文摘要
Project Summary Breast cancer is a significant healthcare and social-economical problem. The primary objective is to develop a quantitative, noninvasive technique that enables accurate characterization of breast tumors by incorporation of local shear deformation. The technique could be integrated into 3D automated breast ultrasound (ABUS) scanner or conventional 2D ultrasound scanners, in a way which could provide clinically relevant information for lesion differentiation and management during diagnosis, treatment planning, and post-treatment evaluation. Specific research aims are: (1) improve displacement measurements by developing a novel physics-based denoising algorithm as a post- processing tool, (2) investigate novel metrics to accurately quantify local ultrasound strain elastography-derived shear deformation and (3) determine improved usefulness of elastography- based analytics. An integral plan of this AREA proposal is also to mentor and encourage undergraduate students to pursue careers in quantitative biomedical engineering through impactful cancer imaging research. To establish the feasibility, computer-simulated ultrasound elastography data and in vivo 2D and 3D ultrasound data involving biopsy-confirmed breast lesions will be used to validate our approach. If feasibility is established, a follow-up project is planned to examine the clinical utility of this technique in a prospective clinical study by integrating all developed techniques into an ABUS scanner. This AREA proposal may also make impacts on Michigan Technological University by providing resources for training undergraduate students and building a nationally recognized research and educational program in human healthcare.
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Personalized Management of Intracranial Aneurysms Using Computer-aided Analytics
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