Automatic Liver Lesion Detection using Cascaded Deep Residual Networks

10 April 2017

Papers citing "Automatic Liver Lesion Detection using Cascaded Deep Residual Networks"

7 / 7 papers shown

Title
Deep residual learning with product units Ziyuan Li U. Jaekel B. Dellen 62 0 0 07 May 2025
Hierarchical Deep Network with Uncertainty-aware Semi-supervised Learning for Vessel Segmentation Chenxin Li Wenao Ma Liyan Sun Xinghao Ding Yue Huang Guisheng Wang Yizhou Yu 20 36 0 31 May 2021
SAR-U-Net: squeeze-and-excitation block and atrous spatial pyramid pooling based residual U-Net for automatic liver segmentation in Computed Tomography Jinke Wang Peiqing Lv Haiying Wang Changfa Shi SSeg 25 103 0 11 Mar 2021
RA-UNet: A hybrid deep attention-aware network to extract liver and tumor in CT scans Qiangguo Jin Zhao-Peng Meng Changming Sun Leyi Wei R. Su MedIm 29 354 0 04 Nov 2018
Conditional Generative Refinement Adversarial Networks for Unbalanced Medical Image Semantic Segmentation Mina Rezaei Haojin Yang Christoph Meinel GAN SSeg MedIm 22 21 0 09 Oct 2018
Liver Lesion Detection from Weakly-labeled Multi-phase CT Volumes with a Grouped Single Shot MultiBox Detector Sang-gil Lee J. S. Bae Hyunjae Kim J. H. Kim Sungroh Yoon 19 30 0 02 Jul 2018
Wider or Deeper: Revisiting the ResNet Model for Visual Recognition Zifeng Wu Chunhua Shen Anton Van Den Hengel SSeg 260 1,495 0 30 Nov 2016