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Classification of oral lesions using deep learning for early detection of oral cancer

Classification of oral lesions using deep learning for early detection of oral cancer
使用深度学习对口腔病变进行分类以早期发现口腔癌
批准号:
MR/S013865/1
负责人:
Sarah Barman
金额:
$18.72万
依托单位:
依托单位国家:
英国
项目类别:
Research Grant
财政年份:
2018
资助国家:
英国
项目状态:
已结题
起止时间:
2018 至 --

项目摘要

项目成果

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中文摘要
翻译
对于大多数癌症来说,早期发现会带来更好的存活率。口腔癌是为数不多的可见癌症之一,其中许多癌症之前都有潜在的恶性病变,医疗干预可以防止癌症的发展。总而言之,口腔癌提供了一个及早发现的机会。然而,如果没有专门的培训,确定哪种口腔病变有患口腔癌的倾向并不容易,而且这个问题由于缺乏受过这方面专门知识培训的专家而变得复杂,特别是在大多数口腔癌症都被诊断出来的低收入和中等收入国家。克服这一问题的一种创新方法是开发一种人工智能算法,将口腔病变分为良性病变和潜在恶性或隐匿性癌症,以便对患者进行相应的分诊,以接受适当的临床处理。在这个项目中,我们建议在一个多学科的国际团队中工作,从现有和未来的收藏中整理一个图像库,这将促进人工智能算法的开发,并将进行测试和验证。该项目的结果将为进一步严格的测试、开发包含该自动化工具的应用程序以及口腔癌早期检测的临床验证铺平道路。口腔病变自动分类工具的开发将有助于确定最有可能罹患口腔癌的患者,以便对这些患者进行适当的管理。该项目在低收入和中等收入国家特别有影响,因为全球口腔癌的大部分负担都在这些国家。
英文摘要
For the majority of cancers, early detection results in better survival. Oral cancer is one of the few cancers that is visible and many of these cancers are preceded by a potentially malignant lesion where medical intervention can prevent the development of cancer. Taken together, oral cancer presents an opportunity for early detection. However, identifying which oral lesion has a propensity to become oral cancer is not straightforward without specialised training and this problem is confounded by the lack of specialists who are trained in this expertise particularly in low- and middle-income countries, where the majority of oral cancers are diagnosed. One innovative approach to overcome this is to develop an artificial intelligence algorithm to classify oral lesions into those that are benign and those that are potentially malignant or are occult cancer so that patients can be triaged accordingly to receive appropriate clinical management. In this project, we propose to work within a multi-disciplinary, international team to collate a library of images from existing and prospective collections that will facilitate the development of an artificial intelligence algorithm that will be tested and validated. The outcome of this project will pave the way for further rigorous testing, development of an App incorporating this automated tool and clinical validation for the early detection of oral cancer. The development of an automated tool for the classification of oral lesions will facilitate the identification of patients most at risk to develop oral cancer so that these individuals can be managed appropriately. This project is particularly impactful in the low- and middle-income countries as the majority of the global burden of oral cancer is found in these countries.
期刊论文(5)
专著(0)
科研奖励(0)
会议论文
Image collection and annotation platforms to establish a multi-source database of oral lesions.
图像采集和标注平台,建立口腔病变多源数据库。
DOI: 10.1111/odi.14206
发表时间: 2023
期刊: Oral diseases
影响因子: 3.8
作者: [Rajendran S]
通讯作者: Rajendran S
DOI: 10.1109/access.2020.3010180
发表时间: 2020-01-01
期刊: IEEE ACCESS
影响因子: 3.9
作者: [Welikala, Roshan Alex, Remagnino, Paolo, Barman, Sarah Ann]
通讯作者: Barman, Sarah Ann
Medical Image Understanding and Analysis - 25th Annual Conference, MIUA 2021, Oxford, United Kingdom, July 12-14, 2021, Proceedings
医学图像理解与分析 - 第 25 届年会,MIUA 2021,英国牛津,2021 年 7 月 12-14 日,会议记录
DOI: 10.1007/978-3-030-80432-9_17
发表时间: 2021
期刊:
影响因子: --
作者: [Bagur A]
通讯作者: Bagur A
国内基金
海外基金
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  • 资助金额:
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  • 负责人:
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  • 项目类别:
    面上项目
  • 资助金额:
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  • 批准年份:
    2023
  • 负责人:
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  • 依托单位:
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