The DFUC 2020 Dataset: Analysis Towards Diabetic Foot Ulcer Detection.

TouchREVIEWS in endocrinology Pub Date : 2021-04-01 Epub Date: 2021-04-28 DOI:10.17925/EE.2021.17.1.5
Bill Cassidy, Neil D Reeves, Joseph M Pappachan, David Gillespie, Claire O'Shea, Satyan Rajbhandari, Arun G Maiya, Eibe Frank, Andrew Jm Boulton, David G Armstrong, Bijan Najafi, Justina Wu, Rupinder Singh Kochhar, Moi Hoon Yap
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引用次数: 0

Abstract

Every 20 seconds a limb is amputated somewhere in the world due to diabetes. This is a global health problem that requires a global solution. The International Conference on Medical Image Computing and Computer Assisted Intervention challenge, which concerns the automated detection of diabetic foot ulcers (DFUs) using machine learning techniques, will accelerate the development of innovative healthcare technology to address this unmet medical need. In an effort to improve patient care and reduce the strain on healthcare systems, recent research has focused on the creation of cloud-based detection algorithms. These can be consumed as a service by a mobile app that patients (or a carer, partner or family member) could use themselves at home to monitor their condition and to detect the appearance of a DFU. Collaborative work between Manchester Metropolitan University, Lancashire Teaching Hospitals and the Manchester University NHS Foundation Trust has created a repository of 4,000 DFU images for the purpose of supporting research toward more advanced methods of DFU detection. This paper presents a dataset description and analysis, assessment methods, benchmark algorithms and initial evaluation results. It facilitates the challenge by providing useful insights into state-of-the-art and ongoing research.

DFUC 2020 数据集:糖尿病足溃疡检测分析
每 20 秒钟,世界上就有一个地方因糖尿病而截肢。这是一个全球性的健康问题,需要全球性的解决方案。医学影像计算和计算机辅助干预国际会议的挑战是利用机器学习技术自动检测糖尿病足溃疡(DFUs),它将加速创新医疗保健技术的发展,以满足这一尚未得到满足的医疗需求。为了改善患者护理并减轻医疗系统的压力,最近的研究重点是创建基于云的检测算法。患者(或护理人员、伴侣或家人)可以在家中使用手机应用程序来监测自己的病情并检测是否出现 DFU。曼彻斯特都会大学、兰开夏教学医院和曼彻斯特大学 NHS 基金会信托基金会合作建立了一个包含 4000 张 DFU 图像的存储库,以支持对更先进的 DFU 检测方法的研究。本文介绍了数据集描述和分析、评估方法、基准算法和初步评估结果。通过对最新技术和正在进行的研究提供有用的见解,它有助于应对挑战。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
2.40
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