SegTHOR: Segmentation of Thoracic Organs at Risk in CT images

Variations in the contouring of organs at risk: test case from a patient with oropharyngeal cancer

Benjamin E Nelms, Wolfgang A Tomé, Greg Robinson, and James Wheeler · 2012

Earlier work this paper cites.

Multiatlas segmentation of thoracic and abdominal anatomy with level set-based local search

Eduard Schreibmann, David M Marcus, and Tim Fox · 2014

Earlier work this paper cites.

Dropout: A Simple Way to Prevent Neural Networks from Overfitting

Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov · 2014

Earlier work this paper cites.

Segmentation of organs at risk in CT volumes of head, thorax, abdomen, and pelvis

Miaofei Han, Jinfeng Ma, Yan Li, Meiling Li, Yanli Song, and Qiang Li · 2015

Earlier work this paper cites.

Fully Convolutional Networks for Semantic Segmentation

Jonathan Long, Evan Shelhamer, and Trevor Darrell · 2015

Earlier work this paper cites.

U-Net: Convolutional Networks for Biomedical Image Segmentation

Olaf Ronneberger, Philipp Fischer, and Thomas Brox · 2015

Earlier work this paper cites.

3D U-Net: Learning Dense Volumetric Segmentation from Sparse Annotation

Özgün Çiçek, Ahmed Abdulkadir, Soeren S. Lienkamp, Thomas Brox, and Olaf Ronneberger · 2016

Earlier work this paper cites.

3d Deeply Supervised Network for Automatic Liver Segmentation from CT volumes

Original

Qi Dou, Hao Chen, Yueming Jin, Lequan Yu, Jing Qin, and Pheng-Ann Heng · 2016

Cited alongside, same era.

V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation

Fausto Milletari, Nassir Navab, and Seyed-Ahmad Ahmadi · 2016

Cited alongside, same era.

A review of interventions to reduce inter-observer variability in volume delineation in radiation oncology

Shalini K Vinod, Myo Min, Michael G Jameson, and Lois C Holloway · 2016

Cited alongside, same era.

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

Liang-Chieh Chen, George Papandreou, Iasonas Kokkinos, Kevin Murphy, and Alan L Yuille · 2017

Cited alongside, same era.

H-denseunet: Hybrid densely connected unet for liver and liver tumor segmentation from CT volumes

Original

Generalised Dice overlap as a deep learning loss function for highly unbalanced segmentations

Original

Carole H. Sudre, Wenqi Li, Tom Vercauteren, Sébastien Ourselin, and M. Jorge Cardoso · 2017

Later among the works it cites.

Segmentation of Organs at Risk in thoracic CT images using a SharpMask architecture and Conditional Random Fields

Roger Trullo, Caroline Petitjean, Su Ruan, Bernard Dubray, Dong Nie, and Dinggang Shen · 2017

Later among the works it cites.

Deep learning to achieve clinically applicable segmentation of head and neck anatomy for radiotherapy

Original

Stanislav Nikolov, Sam Blackwell, Ruheena Mendes, Jeffrey De Fauw, Clemens Meyer, Cían Hughes, Harry Askham, Bernardino Romera-Paredes, Alan Karthikesalingam, Carlton Chu, et al · 2018

Later among the works it cites.

Handling missing annotations for semantic segmentation with deep convnets

Olivier Petit, Nicolas Thome, Arnaud Charnoz, Alexandre Hostettler, and Luc Soler · 2018

Later among the works it cites.