Nie Meng-Yuan, An Xin-Wei, Xing Yun-Can, Wang Zheng, Wang Yan-Qiu, Lü Jia-Qi
Center for Advanced Laser Technology, Hebei University of Technology Tianjin, China.
Hebei Key Laboratory of Advanced Laser Technology and Equipment Tianjin, China.
Am J Cancer Res. 2024 Nov 15;14(11):5456-5470. doi: 10.62347/BZIZ6358. eCollection 2024.
Colorectal cancer (CRC) is one of the most common cancers worldwide. Early detection and removal of colorectal polyps during colonoscopy are crucial for preventing such cancers. With the development of artificial intelligence (AI) technology, it has become possible to detect and localize colorectal polyps in real time during colonoscopy using computer-aided diagnosis (CAD). This provides a reliable endoscopist reference and leads to more accurate diagnosis and treatment. This paper reviews AI-based algorithms for real-time detection of colorectal polyps, with a particular focus on the development of deep learning algorithms aimed at optimizing both efficiency and correctness. Furthermore, the challenges and prospects of AI-based colorectal polyp detection are discussed.
结直肠癌(CRC)是全球最常见的癌症之一。在结肠镜检查期间早期发现并切除大肠息肉对于预防此类癌症至关重要。随着人工智能(AI)技术的发展,利用计算机辅助诊断(CAD)在结肠镜检查期间实时检测和定位大肠息肉已成为可能。这为内镜医师提供了可靠的参考,并有助于实现更准确的诊断和治疗。本文综述了基于人工智能的大肠息肉实时检测算法,特别关注旨在优化效率和准确性的深度学习算法的发展。此外,还讨论了基于人工智能的大肠息肉检测所面临的挑战和前景。