A Comprehensive Systematic Review of YOLO for Medical Object Detection (2018 to 2023)

被引:78
作者
Ragab, Mohammed Gamal [1 ,2 ]
Abdulkadir, Said Jadid [1 ,2 ]
Muneer, Amgad [1 ]
Alqushaibi, Alawi [1 ,2 ]
Sumiea, Ebrahim Hamid [1 ,2 ]
Qureshi, Rizwan [3 ]
Al-Selwi, Safwan Mahmood [1 ,2 ]
Alhussian, Hitham [1 ,2 ]
机构
[1] Univ Teknol PETRONAS, Dept Comp & Informat Sci, Seri Iskandar 32610, Malaysia
[2] Univ Teknol PETRONAS, Ctr Res Data Sci, Seri Iskandar 32610, Malaysia
[3] Natl Univ Comp & Emerging Sci, Fast Sch Comp, Karachi 75030, Pakistan
关键词
YOLO; healthcare applications; artificial intelligence; medical object detection; medical imaging; systematic review; COMPUTER-AIDED DIAGNOSIS;
D O I
10.1109/ACCESS.2024.3386826
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
YOLO (You Only Look Once) is an extensively utilized object detection algorithm that has found applications in various medical object detection tasks. This has been accompanied by the emergence of numerous novel variants in recent years, such as YOLOv7 and YOLOv8. This study encompasses a systematic exploration of the PubMed database to identify peer-reviewed articles published between 2018 and 2023. The search procedure found 124 relevant studies that employed YOLO for diverse tasks including lesion detection, skin lesion classification, retinal abnormality identification, cardiac abnormality detection, brain tumor segmentation, and personal protective equipment detection. The findings demonstrated the effectiveness of YOLO in outperforming alternative existing methods for these tasks. However, the review also unveiled certain limitations, such as well-balanced and annotated datasets, and the high computational demands. To conclude, the review highlights the identified research gaps and proposes future directions for leveraging the potential of YOLO for medical object detection.
引用
收藏
页码:57815 / 57836
页数:22
相关论文
共 131 条
[1]   Automatic localization of normal active organs in 3D PET scans [J].
Afshari, Saeedeh ;
BenTaieb, Aicha ;
Hamarneh, Ghassan .
COMPUTERIZED MEDICAL IMAGING AND GRAPHICS, 2018, 70 :111-118
[2]   Hierarchical approach for pulmonary-nodule identification from CT images using YOLO model and a 3D neural network classifier [J].
Ahmadyar, Yashar ;
Kamali-Asl, Alireza ;
Arabi, Hossein ;
Samimi, Rezvan ;
Zaidi, Habib .
RADIOLOGICAL PHYSICS AND TECHNOLOGY, 2024, 17 (01) :124-134
[3]   Evaluation of deep learning detection and classification towards computer-aided diagnosis of breast lesions in digital X-ray mammograms [J].
Al-antari, Mugahed A. ;
Han, Seung-Moo ;
Kim, Tae-Seong .
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2020, 196
[4]   Deep Learning Computer-Aided Diagnosis for Breast Lesion in Digital Mammogram [J].
Al-antari, Mugahed A. ;
Al-masni, Mohammed A. ;
Kim, Tae-Seong .
DEEP LEARNING IN MEDICAL IMAGE ANALYSIS: CHALLENGES AND APPLICATIONS, 2020, 1213 :59-72
[5]   Automated detection of cerebral microbleeds in MR images: A two-stage deep learning approach [J].
Al-masni, Mohammed A. ;
Kim, Woo-Ram ;
Kim, Eung Yeop ;
Noh, Young ;
Kim, Dong-Hyun .
NEUROIMAGE-CLINICAL, 2020, 28
[6]   Machine Learning Models for the Identification of Prognostic and Predictive Cancer Biomarkers: A Systematic Review [J].
Al-Tashi, Qasem ;
Saad, Maliazurina B. ;
Muneer, Amgad ;
Qureshi, Rizwan ;
Mirjalili, Seyedali ;
Sheshadri, Ajay ;
Le, Xiuning ;
Vokes, Natalie I. ;
Zhang, Jianjun ;
Wu, Jia .
INTERNATIONAL JOURNAL OF MOLECULAR SCIENCES, 2023, 24 (09)
[7]  
Albawi S, 2017, I C ENG TECHNOL
[8]   YOLO-Based Deep Learning Model for Pressure Ulcer Detection and Classification [J].
Aldughayfiq, Bader ;
Ashfaq, Farzeen ;
Jhanjhi, N. Z. ;
Humayun, Mamoona .
HEALTHCARE, 2023, 11 (09)
[9]   Deep Learning Models for Classification of Dental Diseases Using Orthopantomography X-ray OPG Images [J].
Almalki, Yassir Edrees ;
Din, Amsa Imam ;
Ramzan, Muhammad ;
Irfan, Muhammad ;
Aamir, Khalid Mahmood ;
Almalki, Abdullah ;
Alotaibi, Saud ;
Alaglan, Ghada ;
Alshamrani, Hassan A. ;
Rahman, Saifur .
SENSORS, 2022, 22 (19)
[10]   YOLO Based Breast Masses Detection and Classification in Full-Field Digital Mammograms [J].
Aly, Ghada Hamed ;
Marey, Mohammed ;
El-Sayed, Safaa Amin ;
Tolba, Mohamed Fahmy .
COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE, 2021, 200 (200)