Deep learning (DL) has become widely used for medical image segmentation in recent
years. However, despite these advances, there are still problems for which DL-based …

摘要近年来, 随着深度学习技术的发展, 深度神经网络在医学图像分割领域得到了广泛应用.
其中, U-Net 以其良好的分割性能, 逐渐成为图像分割领域的研究热点. 根据相关研究工作 …

Automatic segmentation of glioma and its subregions is of great significance for diagnosis,
treatment and monitoring of disease. In this paper, an augmentation method, called …

目的针对目前基于深度学习的脑肿瘤分割算法参数量大, 计算复杂和快速性差的问题,
提出了一种超轻量级快速语义分割网络LRUNet (lightweight rapid UNet) …

摘要肝脏肿瘤的精确分割是肝脏疾病诊断, 手术计划和术后评估的重要步骤. 计算机断层成像(
computed tomography, CT) 能够为肝脏肿瘤的诊断和治疗提供更为全面的信息 …

目的针对现有神经网络模型需要对左心室心肌内膜和外膜单独建模的问题, 本文提出了一种基于
胶囊结构的心脏磁共振图像(magnetic resonance imaging, MRI) 分割模型Seg-CapNet …

Computer-aided brain tumor segmentation using magnetic resonance imaging (MRI) is of
great significance for the clinical diagnosis and treatment of patients. Recently, U-Net has …

目的脑肿瘤是一种严重威胁人类健康的疾病. 利用计算机辅助诊断进行脑肿瘤分割对于患者的
预后和治疗具有重要的临床意义. 3D 卷积神经网络因具有空间特征提取充分 …

To improve the accuracy of image detail structure segmentation is a challenging research
topic. In this paper, a progressively refined image semantics segmentation method based on …

目的超声弹性成像技术已逐步应用于支气管淋巴结良恶性的诊断, 帮助确定肺癌分期.
在支气管超声弹性图像中, 淋巴结区域的精确定位对诊断准确度具有重要影响 …