Hybrid dilation and attention residual U-Net for medical image segmentation

MV-RAN: Multiview recurrent aggregation network for echocardiographic sequences segmentation and full cardiac cycle analysis

(2020) Ming Li et al.   COMPUTERS IN BIOLOGY AND MEDICINE

RA-UNet: A Hybrid Deep Attention-Aware Network to Extract Liver and Tumor in CT Scans

(2020) Qiangguo Jin et al.   Frontiers in Bioengineering and Biotechnology

Fully Convolutional Networks for Semantic Segmentation of Very High Resolution Remotely Sensed Images Combined With DSM

(2018) Weiwei Sun et al.   IEEE Geoscience and Remote Sensing Letters

DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs

(2018) Liang-Chieh Chen et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

DRUNET: a dilated-residual U-Net deep learning network to segment optic nerve head tissues in optical coherence tomography images

(2018) Sripad Krishna Devalla et al.   Biomedical Optics Express

QuickNAT: A fully convolutional network for quick and accurate segmentation of neuroanatomy

(2018) Abhijit Guha Roy et al.   NEUROIMAGE

SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image Segmentation

(2017) Vijay Badrinarayanan et al.   IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE

Crowdsourcing the creation of image segmentation algorithms for connectomics

(2015) Ignacio Arganda-Carreras et al.   Frontiers in Neuroanatomy