基于深度学习的食管镜下肠化生定位与识别

Cong Wang, Ya Li, Jianning Yao, Bing Chen, Jiayou Song, Xiaonan Yang
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引用次数: 7

摘要

肠化生是一种癌前病变,胃癌是一种非常常见的恶性肿瘤,每年都有很多人死于胃癌。胃癌的早期诊断对于降低患者死亡率和整体医疗负担至关重要。然而,传统的内镜下胃粘膜肠皮化生缺乏特异性表现。因此,癌前肠化生的细微变化并不明显,限制了诊断的准确性。作为临床早期胃癌诊断的计算机辅助工具,我们提出了一种用于肠化生病变识别和定位的深度学习框架模型W-Deeplab。实现了对内窥镜图像的高精度语义分割。作为临床医生的计算机辅助工具,可提高肠化生诊断的准确性和效率,减少误诊。
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Localizing and Identifying Intestinal Metaplasia Based on Deep Learning in Oesophagoscope
Intestinal metaplasia is a precancerous lesion, gastric cancer is a very common malignant tumor, and many people die every year from stomach cancer. Early diagnosis of gastric cancer is critical to reducing patient mortality and overall medical burden. However, traditional endoscopic intestinal metaplasia on the gastric mucosa lacks specific performance. Consequently, subtle changes in precancerous intestinal metaplasia are not obvious limiting diagnostic accuracy. As a clinical computer aid in the diagnosis of early gastric cancer, a deep learning framework model called W-Deeplab was proposed for the identification and localization of intestinal metaplasia lesions. It achieves high-precision semantic segmentation of endoscopic images. As a computer aid to clinicians, it can improve the accuracy and efficiency of intestinal metaplasia diagnosis and reduce misdiagnosis.
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