Dense convolutional network (DenseNet) is a hot topic in deep learning research in recent
years, which has good applications in medical image analysis. In this paper, DenseNet is …

Shortly after deep learning algorithms were applied to Image Analysis, and more importantly
to medical imaging, their applications increased significantly to become a trend. Likewise …

In this study, multiple lung diseases are diagnosed with the help of the Neural Network
algorithm. Specifically, Emphysema, Infiltration, Mass, Pleural Thickening, Pneumonia …

Existing multi-label medical image learning tasks generally contain rich relationship
information among pathologies such as label co-occurrence and interdependency, which is …

Inspired by the biological evolution, this paper proposes an evolutionary synthesis
mechanism to automatically evolve DenseNet towards high sparsity and efficiency for …

残差神经网络(ResNet) 是深度学习领域的研究热点, 广泛应用于医学图像处理领域.
该文对残差神经网络从以下几个方面进行综述: 首先, 阐述残差神经网络的基本原理和模型结构; …

Background Deep learning (DL), a subset of artificial intelligence (AI), has been applied to
pneumothorax diagnosis to aid physician diagnosis, but no meta-analysis has been …

Chest X‐ray (CXR) imaging is one of the most widely used and economical tests to
diagnose a wide range of diseases. However, even for expert radiologists, it is a challenge …

Automatic biomedical image segmentation plays an important role in speeding up disease
detection and diagnosis. The rapid development of Deep Learning has shown ground …

Automated multi-label chest X-ray (CXR) image classification has recently made significant
progress in clinical diagnosis based on the advanced deep learning techniques. However …