论文标题
审查胃癌的计算机视觉：诊断的潜在有效工具
Review on Computer Vision in Gastric Cancer: Potential Efficient Tools for Diagnosis
论文作者
论文摘要
对于临床医生来说，快速诊断胃癌是一个巨大的挑战。最近已经取得了胃癌的计算机视觉进展，这篇综述着重于过去五年的进步。提出了不同的数据生成和增强方法，并进行了各种提取歧视性特征的方法。仔细讨论分类和分割技术，以帮助更精确的诊断和及时治疗。为了进行分类，已经开发出各种方法来更好地进行特定图像，例如具有旋转的图像和实时估计的（内窥镜），高分辨率图像（组织病理学），低诊断精度图像（X射线），与腔体软组织（CT）的较差的对比度图像或那些具有足够的注释的图像。为了进行检测和细分，比较了传统方法和机器学习方法。这些方法的应用将大大减少胃癌诊断的人工和时间消耗。
Rapid diagnosis of gastric cancer is a great challenge for clinical doctors. Dramatic progress of computer vision on gastric cancer has been made recently and this review focuses on advances during the past five years. Different methods for data generation and augmentation are presented, and various approaches to extract discriminative features compared and evaluated. Classification and segmentation techniques are carefully discussed for assisting more precise diagnosis and timely treatment. For classification, various methods have been developed to better proceed specific images, such as images with rotation and estimated real-timely (endoscopy), high resolution images (histopathology), low diagnostic accuracy images (X-ray), poor contrast images of the soft-tissue with cavity (CT) or those images with insufficient annotation. For detection and segmentation, traditional methods and machine learning methods are compared. Application of those methods will greatly reduce the labor and time consumption for the diagnosis of gastric cancers.
