MedBin: A lightweight End-to-End model-based method for medical waste management

IF 7.1 2区 环境科学与生态学 Q1 ENGINEERING, ENVIRONMENTAL Waste management Pub Date : 2025-03-14 DOI:10.1016/j.wasman.2025.114742
Xiazhen Xu , Chenyang Wang , Qiufeng Yi , Jiaqi Ye , Xiangfei Kong , Shazad Q Ashraf , Karl D. Dearn , Amir M. Hajiyavand
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Abstract

The surge in medical waste has highlighted the urgent need for cost-effective and advanced management solutions. In this paper, a novel medical waste management approach, “MedBin,” is proposed for automated sorting, reusing, and recycling. A comprehensive medical waste dataset, ”MedBin-Dataset“ is established, comprising 2,119 original images spanning 36 categories, with samples captured in various backgrounds. The lightweight ”MedBin-Net“ model is introduced to enable detection and instance segmentation of medical waste, enhancing waste recognition capabilities. Experimental results demonstrate the effectiveness of the proposed approach, achieving an average precision of 0.91, recall of 0.97, and F1-score of 0.94 across all categories with just 2.51 M parameters (where M stands for million, i.e., 2.51 million parameters), 5.20G FLOPs (where G stands for billion, i.e., 5.20 billion floating-point operations per second), and 0.60 ms inference time. Additionally, the proposed method includes a World Health Organization (WHO) Guideline-Based Classifier that categorizes detected waste into 5 types, each with a corresponding disposal method, following WHO medical waste classification standards. The proposed method, along with the dedicated dataset, offers a promising solution that supports sustainable medical waste management and other related applications. To access the MedBin-Dataset samples, please visit https://universe.roboflow.com/uob-ylti8/medbin_dataset. The source code for MedBin-Net can be found at https://github.com/Wayne3918/MedbinNet.
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医疗废物的激增凸显了对具有成本效益的先进管理解决方案的迫切需求。本文提出了一种新型医疗废物管理方法 "MedBin",用于自动分类、再利用和回收。本文建立了一个全面的医疗废物数据集 "MedBin-Dataset",由 2,119 张原始图像组成,涵盖 36 个类别,并在不同背景下采集样本。引入轻量级 "MedBin-Net "模型,实现医疗废物的检测和实例分割,提高废物识别能力。实验结果证明了所提方法的有效性,在所有类别中平均精确度为 0.91,召回率为 0.97,F1 分数为 0.94,参数数为 251 万(其中 M 代表百万,即 251 万个参数),浮点运算次数为 5.20G(其中 G 代表十亿,即每秒 52 亿次浮点运算),推理时间为 0.60 毫秒。此外,拟议方法还包括一个基于世界卫生组织(WHO)指南的分类器,该分类器按照世界卫生组织的医疗废物分类标准,将检测到的废物分为 5 种类型,每种类型都有相应的处置方法。建议的方法与专用数据集一起,为支持可持续医疗废物管理和其他相关应用提供了一个前景广阔的解决方案。要访问 MedBin 数据集样本,请访问 https://universe.roboflow.com/uob-ylti8/medbin_dataset。MedBin-Net 的源代码可在 https://github.com/Wayne3918/MedbinNet 上找到。
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来源期刊
Waste management
Waste management 环境科学-工程:环境
CiteScore
15.60
自引率
6.20%
发文量
492
审稿时长
39 days
期刊介绍: Waste Management is devoted to the presentation and discussion of information on solid wastes,it covers the entire lifecycle of solid. wastes. Scope: Addresses solid wastes in both industrialized and economically developing countries Covers various types of solid wastes, including: Municipal (e.g., residential, institutional, commercial, light industrial) Agricultural Special (e.g., C and D, healthcare, household hazardous wastes, sewage sludge)
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