12 citations · 21 across the 5 of their papers we have counts for
5 papers
FU-net: Multi-class Image Segmentation Using Feedback Weighted U-net
Mina Jafari, Ruizhe Li, Yue Xing +4
In this paper, we present a generic deep convolutional neural network (DCNN) for multi-class image segmentation. It is based on a well-established supervised end-to-end DCNN model,…
DRU-net: An Efficient Deep Convolutional Neural Network for Medical Image Segmentation
Mina Jafari, Dorothee Auer, Susan Francis +2
Residual network (ResNet) and densely connected network (DenseNet) have significantly improved the training efficiency and performance of deep convolutional neural networks (DCNNs)…
A Spatially Constrained Deep Convolutional Neural Network for Nerve Fiber Segmentation in Corneal Confocal Microscopic Images using Inaccurate Annotations
Ning Zhang, Susan Francis, Rayaz Malik +1
Semantic image segmentation is one of the most important tasks in medical image analysis. Most state-of-the-art deep learning methods require a large number of accurately annotated…
A generic ensemble based deep convolutional neural network for semi-supervised medical image segmentation
Ruizhe Li, Dorothee Auer, Christian Wagner +1
Deep learning based image segmentation has achieved the state-of-the-art performance in many medical applications such as lesion quantification, organ detection, etc. However, most…
Dual Adaptive Pyramid Network for Cross-Stain Histopathology Image Segmentation
Xianxu Hou, Jingxin Liu, Bolei Xu +6
Supervised semantic segmentation normally assumes the test data being in a similar data domain as the training data. However, in practice, the domain mismatch between the training…