SBIR Phase I: Digitizing The Pathologist In The Operating Room
SBIR Phase I: Digitizing The Pathologist In The Operating Room
批准号:
2126919
负责人:
Jason Hawkes
金额:
$25.6万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2022
资助国家:
美国
项目状态:
已结题
起止时间:
2022-01-15 至 2023-12-31
中文摘要
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英文摘要
The broader impact /commercial potential of this Small Business Innovation Research (SBIR) Phase I project is to improve the quality and reproducibility of cancer diagnosis and margin screening.Surgery currently represents the best opportunity for curing invasive cancers but is limited by modern pathology methods. Mohs surgery is the treatment of choice for skin cancer because it results in the highest cure rates, but it often takes place in stages, extending surgical procedures. The use of ex vivo confocal microscopy (XVM) is potentially faster, less costly, and inherently both 3-D and digitized, with benefits including: 1) enhanced accuracy, precision, and margin control via enriched 3D information content and simplified specimen orientation maintenance, decreasing error and improving functional outcomes; 2) decreased duration of open surgical wounds potentially reducing the rate of complications; and (3) enhanced and accelerated surgical workflows.This Small Business Innovation Research (SBIR) Phase I project aims to improve Mohs surgery and other margin screening applications. Using confocal image processing software, the proposed software will improve current pathology processing methods by enabling rapid processing and re-coloring of XVM images, visualization without the need for retraining, and automated detection of residual tumor at the patient’s bedside, all within minutes. The research described here will result in the production of a fully functional and robust software product through the following development projects: 1) Artificial intelligence (AI)-based software for image preprocessing and colorization/enhancement, and 2) AI-based software for automated identification of key morphological features and diagnosis of basal cell and squamous cell carcinoma. The proposed technology will streamline cancer specimen processing, ultimately improving patient outcomes.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
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