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Boundary Refinement Using Adversarial Learning: Application to Lung Tumor Segmentation in Thoracic MRI

https://doi.org/10.2139/ssrn.3990566
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Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1002/mp.12690openalex-extracted
Segmentation and tracking of lung nodules via graph‐cuts incorporating shape prior and motion from 4D CT
inferredcites →https://doi.org/10.1007/978-3-030-00889-5_30openalex-extracted
SCAN: Structure Correcting Adversarial Network for Organ Segmentation in Chest X-Rays
inferredcites →https://doi.org/10.1007/978-3-030-59719-1_17openalex-extracted
Pay More Attention to Discontinuity for Medical Image Segmentation
inferredcites →https://doi.org/10.1007/978-3-319-24574-4_28openalex-extracted
U-Net: Convolutional Networks for Biomedical Image Segmentation
inferredcites →https://doi.org/10.1007/978-3-642-33418-4_43openalex-extracted
A 4D Statistical Shape Model for Automated Segmentation of Lungs with Large Tumors
inferredcites →https://doi.org/10.1007/978-3-658-40442-0_9openalex-extracted
Generative Adversarial Nets
inferredcites →https://doi.org/10.1016/j.compbiomed.2018.03.015openalex-extracted
3-D segmentation of lung nodules using hybrid level sets
inferredcites →https://doi.org/10.1016/j.ctro.2020.06.002openalex-extracted
A review of the role of MRI in diagnosis and treatment of early stage lung cancer
inferredcites →https://doi.org/10.1016/j.ijleo.2018.08.086openalex-extracted
Improved U-NET network for pulmonary nodules segmentation
inferredcites →https://doi.org/10.1016/j.lungcan.2003.08.004openalex-extracted
CT and MRI for staging of locally advanced non-small cell lung cancer
inferredcites →https://doi.org/10.1016/j.media.2019.101552openalex-extracted
Generative adversarial network in medical imaging: A review
inferredcites →https://doi.org/10.1109/access.2018.2808938openalex-extracted
cC-GAN: A Robust Transfer-Learning Framework for HEp-2 Specimen Image Segmentation
inferredcites →https://doi.org/10.1109/tip.2013.2282899openalex-extracted
A Novel Approach for Lung Nodules Segmentation in Chest CT Using Level Sets
inferredcites →https://doi.org/10.1109/tmi.2017.2698525openalex-extracted
Tumor Cell Load and Heterogeneity Estimation From Diffusion-Weighted MRI Calibrated With Histological Data: an Example From Lung Cancer
inferredcites →https://doi.org/10.1109/tmi.2018.2857800openalex-extracted
Multiple Resolution Residually Connected Feature Streams for Automatic Lung Tumor Segmentation From CT Images
inferredcites →https://doi.org/10.1166/jmihi.2016.1727openalex-extracted
Tumor Segmentation for Lung 4D-CT Data Using Graph Cuts with Inter-Phase Shape Prior
inferredcites →https://doi.org/10.21037/tlcr.2017.09.02openalex-extracted
Magnetic resonance imaging in precision radiation therapy for lung cancer
inferredcites →https://doi.org/10.3322/caac.21660openalex-extracted
Global Cancer Statistics 2020: GLOBOCAN Estimates of Incidence and Mortality Worldwide for 36 Cancers in 185 Countries
inferredcites →https://doi.org/10.48550/arxiv.1411.1784openalex-extracted
Conditional Generative Adversarial Nets
inferredcites →https://doi.org/10.48550/arxiv.1502.03167openalex-extracted
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
inferredcites →https://doi.org/10.48550/arxiv.1702.08014openalex-extracted
Adversarial Networks for the Detection of Aggressive Prostate Cancer
inferredcites →https://doi.org/10.1007/978-3-030-62469-9_4openalex-snapshot
Lung Cancer Tumor Region Segmentation Using Recurrent 3D-DenseUNet
inferredcites →https://doi.org/10.1007/s12021-018-9377-xopenalex-snapshot
SegAN: Adversarial Network with Multi-scale L1 Loss for Medical Image Segmentation
inferredcites →https://doi.org/10.1109/3dv.2016.79openalex-snapshot
V-Net: Fully Convolutional Neural Networks for Volumetric Medical Image Segmentation
inferredcites →https://doi.org/10.1109/cvpr.2017.632openalex-snapshot
Image-to-Image Translation with Conditional Adversarial Networks
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