论文标题
用于糖尿病足溃疡检测的精致深度学习体系结构
A Refined Deep Learning Architecture for Diabetic Foot Ulcers Detection
论文作者
论文摘要
影响下肢的糖尿病足溃疡（DFU）是糖尿病的主要并发症。每年，由于未能识别DFU并从临床医生那里获得适当的治疗，每年有超过100万糖尿病患者受到截肢。迫切需要使用CAD系统检测DFU。在本文中，我们建议在DFUC2020挑战数据集中使用深度学习方法（有效的架构）检测DFU，该数据集由4,500个DFU图像组成。我们进一步完善了有效的架构，以避免假阴性和假阳性预测。该方法的代码可在https://github.com/manugoyal12345/yet-another-Another-fefticeddet-pytorch获得。
Diabetic Foot Ulcers (DFU) that affect the lower extremities are a major complication of diabetes. Each year, more than 1 million diabetic patients undergo amputation due to failure to recognize DFU and get the proper treatment from clinicians. There is an urgent need to use a CAD system for the detection of DFU. In this paper, we propose using deep learning methods (EfficientDet Architectures) for the detection of DFU in the DFUC2020 challenge dataset, which consists of 4,500 DFU images. We further refined the EfficientDet architecture to avoid false negative and false positive predictions. The code for this method is available at https://github.com/Manugoyal12345/Yet-Another-EfficientDet-Pytorch.
