35 citations · 80 across the 15 of their papers we have counts for
4 papers · 1 filter
Decompose-and-Integrate Learning for Multi-class Segmentation in Medical Images
Yizhe Zhang, Michael T. C. Ying, Danny Z. Chen
Segmentation maps of medical images annotated by medical experts contain rich spatial information. In this paper, we propose to decompose annotation maps to learn disentangled and…
SPDA: Superpixel-based Data Augmentation for Biomedical Image Segmentation
Yizhe Zhang, Lin Yang, Hao Zheng +5
Supervised training a deep neural network aims to "teach" the network to mimic human visual perception that is represented by image-and-label pairs in the training data. Superpixel…
Cascade Decoder: A Universal Decoding Method for Biomedical Image Segmentation
Peixian Liang, Jianxu Chen, Hao Zheng +3
The Encoder-Decoder architecture is a main stream deep learning model for biomedical image segmentation. The encoder fully compresses the input and generates encoded features, and…
CC-Net: Image Complexity Guided Network Compression for Biomedical Image Segmentation
Suraj Mishra, Peixian Liang, Adam Czajka +2
Convolutional neural networks (CNNs) for biomedical image analysis are often of very large size, resulting in high memory requirement and high latency of operations. Searching for…