CE-Net: Context Encoder Network for 2D Medical Image Segmentation

7 Mar 2019Zaiwang GuJun ChengHuazhu FuKang ZhouHuaying HaoYitian ZhaoTianyang ZhangShenghua GaoJiang Liu

Medical image segmentation is an important step in medical image analysis. With the rapid development of convolutional neural network in image processing, deep learning has been used for medical image segmentation, such as optic disc segmentation, blood vessel detection, lung segmentation, cell segmentation, etc... (read more)

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TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK RESULT LEADERBOARD
Retinal Vessel Segmentation DRIVE CE-Net AUC 0.9779 # 5
Accuracy 0.9545 # 2
Medical Image Segmentation ISBI 2012 EM Segmentation CE-Net VInfo 0.9878 # 1
VRand 0.9743 # 1
Lung Nodule Segmentation LUNA CE-Net Accuracy 0.99 # 1
Optic Disc Segmentation Messidor CE-Net Error rate 0.051 # 1
Optic Disc Segmentation ORIGA CE-Net Error rate 0.058 # 1
Optic Disc Segmentation RIM-ONE-R1 CE-Net Error rate 0.087 # 1
Retinal OCT Layer Segmentation Topcon CE-Net w/ Dice MAE 1.68 # 1