LoDoPaB-CT, a benchmark dataset for low-dose computed tomography reconstruction
Published 2021 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
LoDoPaB-CT, a benchmark dataset for low-dose computed tomography reconstruction
Authors
Keywords
-
Journal
Scientific Data
Volume 8, Issue 1, Pages -
Publisher
Springer Science and Business Media LLC
Online
2021-04-16
DOI
10.1038/s41597-021-00893-z
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- NETT: Solving Inverse Problems with Deep Neural Networks
- (2020) Housen Li et al. INVERSE PROBLEMS
- Radon Inversion via Deep Learning
- (2020) Ji He et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- Computed Tomography Reconstruction Using Deep Image Prior and Learned Reconstruction Methods
- (2020) Daniel Otero Baguer et al. INVERSE PROBLEMS
- RecDNN: deep neural network for image reconstruction from limited view projection data
- (2020) Kailash Wamanrao Kalare et al. SOFT COMPUTING
- BIAS: Transparent reporting of biomedical image analysis challenges
- (2020) Lena Maier-Hein et al. MEDICAL IMAGE ANALYSIS
- A cone-beam X-ray computed tomography data collection designed for machine learning
- (2019) Henri Der Sarkissian et al. Scientific Data
- Learned Primal-Dual Reconstruction
- (2018) Jonas Adler et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- Low-Dose CT Image Denoising Using a Generative Adversarial Network With Wasserstein Distance and Perceptual Loss
- (2018) Qingsong Yang et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- 3-D Convolutional Encoder-Decoder Network for Low-Dose CT via Transfer Learning From a 2-D Trained Network
- (2018) Hongming Shan et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- Image Reconstruction is a New Frontier of Machine Learning
- (2018) Ge Wang et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- Modern regularization methods for inverse problems
- (2018) Martin Benning et al. ACTA NUMERICA
- A new dataset of computed-tomography angiography images for computer-aided detection of pulmonary embolism
- (2018) Mojtaba Masoudi et al. Scientific Data
- Deep Convolutional Neural Network for Inverse Problems in Imaging
- (2017) Kyong Hwan Jin et al. IEEE TRANSACTIONS ON IMAGE PROCESSING
- Hybrid Pre-Log and Post-Log Image Reconstruction for Computed Tomography
- (2017) Guobao Wang et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- Comparison Between Pre-Log and Post-Log Statistical Models in Ultra-Low-Dose CT Reconstruction
- (2017) Lin Fu et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- Low-Dose CT With a Residual Encoder-Decoder Convolutional Neural Network
- (2017) Hu Chen et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- Solving ill-posed inverse problems using iterative deep neural networks
- (2017) Jonas Adler et al. INVERSE PROBLEMS
- TU-FG-207A-04: Overview of the Low Dose CT Grand Challenge
- (2016) C. McCollough MEDICAL PHYSICS
- The ASTRA Toolbox: A platform for advanced algorithm development in electron tomography
- (2015) Wim van Aarle et al. ULTRAMICROSCOPY
- The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository
- (2013) Kenneth Clark et al. JOURNAL OF DIGITAL IMAGING
- The Lung Image Database Consortium (LIDC) and Image Database Resource Initiative (IDRI): A Completed Reference Database of Lung Nodules on CT Scans
- (2011) Samuel G. Armato et al. MEDICAL PHYSICS
- Normalized CT Dose Index of the CT Scanners Used in the National Lung Screening Trial
- (2010) Dianna D. Cody et al. AMERICAN JOURNAL OF ROENTGENOLOGY
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExplorePublish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn More