Improving Early Detection & Triage for Oesophageal Cancer with Low-Cost Capsule Endoscopy

改善早期检测

• 批准号: 2268555
• 金额: --
• 依托单位: University of Nottingham
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2019
• 资助国家: 英国
• 起止时间: 2019 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2268555
• 关键词: Improving; Early; Detection; Triage; Oesophageal

Oesophageal cancer has a five year survival rate of 15%. This statistic is so low because early stage cancer in the oesophagus is difficult to detect. The current way of detecting oesophageal cancer is via white light endoscopy and taking biospies of random areas, which can be quiet costly. Therefore, large scale screenings are not an option. The aim of this project is to produce a low cost, pill sized capsule endoscope that can be swallowed by the patient to take advanced images of the oesophagus to screen for signs of oesophageal cancer.A second application of this device is for it to be used in hospital triage to detect blood or blockages in the upper gastrointestinal tract. The goal of this project is to develop a prototype capsule endoscope, at a low cost, to image the oesophagus and detect cancerous tissue. It is desired to image samples of ex-vivo tissue via collaborators at QMC to further develop this device towards its clinical translation.

食道癌的五年存活率为15%。这一统计数据之所以如此之低，是因为早期食道癌很难检测到。目前检测食道癌的方法是通过白光内窥镜检查和对随机区域进行生物显微镜检查，这可能非常昂贵。因此，大规模的放映不是一种选择。该项目的目的是生产一种低成本、药丸大小的胶囊内窥镜，患者可以吞咽它来拍摄食道的高级图像，以筛选食道癌的迹象。该设备的第二个应用是用于医院分诊，以检测上胃肠道的血液或阻塞。该项目的目标是以低成本开发一种胶囊内窥镜原型，以成像食道并检测癌组织。希望通过QMC的合作者对体外组织样本进行成像，以进一步开发这一设备用于临床翻译。

项目成果

Ultra-miniaturised spatial frequency domain imaging for improved early detection of gastrointestinal cancers

• DOI: 10.1117/12.2648766
• 发表时间: 2023-03
• 作者: J. Crowley;G. Gordon

Simulating medical applications of tissue optical property and shape imaging using open-source ray tracing software

• DOI: 10.1117/12.2576779
• 发表时间: 2021-03
• 作者: J. Crowley;George S. D. Gordon

Designing and simulating realistic spatial frequency domain imaging systems using open-source 3D rendering software.

• DOI: 10.1364/boe.484286
• 发表时间: 2023-06-01
• 期刊: BIOMEDICAL OPTICS EXPRESS
• 影响因子: 3.4
• 作者: Crowley, Jane;Gordon, George S. D.
• 通讯作者: Gordon, George S. D.

Training generative adversarial networks for optical property mapping using synthetic image data.

• DOI: 10.1364/boe.458554
• 发表时间: 2022-10-01
• 期刊: BIOMEDICAL OPTICS EXPRESS
• 影响因子: 3.4
• 作者: Osman, A.;Crowley, J.;Gordon, G. S. D.
• 通讯作者: Gordon, G. S. D.

Training Generative Adversarial Networks for Optical Property Mapping using Synthetic Image Data

使用合成图像数据训练生成对抗网络以进行光学属性映射

• DOI: 10.48550/arxiv.2203.07793
• 发表时间: 2022
• 作者: Osman A