On dose cube pixel spacing pre-processing for features extraction stability in dosiomic studies
出版年份 2021 全文链接
标题
On dose cube pixel spacing pre-processing for features extraction stability in dosiomic studies
作者
关键词
Dosiomics, Dose distribution texture analysis, Features stability, Dose cube pixel spacing
出版物
Physica Medica-European Journal of Medical Physics
Volume 90, Issue -, Pages 108-114
出版商
Elsevier BV
发表日期
2021-09-30
DOI
10.1016/j.ejmp.2021.09.010
参考文献
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- (2021) Giulia Buizza et al. Cancers
- Multi‐institutional dose‐segmented dosiomic analysis for predicting radiation pneumonitis after lung stereotactic body radiation therapy
- (2021) Takanori Adachi et al. MEDICAL PHYSICS
- Artificial intelligence: Deep learning in oncological radiomics and challenges of interpretability and data harmonization
- (2021) Panagiotis Papadimitroulas et al. Physica Medica-European Journal of Medical Physics
- Machine learning helps identifying volume-confounding effects in radiomics
- (2020) Alberto Traverso et al. Physica Medica-European Journal of Medical Physics
- Dosiomics improves prediction of locoregional recurrence for intensity modulated radiotherapy treated head and neck cancer cases
- (2020) Aiqian Wu et al. ORAL ONCOLOGY
- Multi-view radiomics and dosiomics analysis with machine learning for predicting acute-phase weight loss in lung cancer patients treated with radiotherapy
- (2020) Sang Ho Lee et al. PHYSICS IN MEDICINE AND BIOLOGY
- The Image Biomarker Standardization Initiative: Standardized Quantitative Radiomics for High-Throughput Image-based Phenotyping
- (2020) Alex Zwanenburg et al. RADIOLOGY
- What is plan quality in radiotherapy? The importance of evaluating dose metrics, complexity, and robustness of treatment plans
- (2020) Victor Hernandez et al. RADIOTHERAPY AND ONCOLOGY
- Dose Distribution Prediction in Isodose Feature‐Preserving Voxelization Domain Using Deep Convolutional Neural Network
- (2019) Ming Ma et al. MEDICAL PHYSICS
- Incorporating dosimetric features into the prediction of 3D VMAT dose distributions using deep convolutional neural network
- (2019) Ming Ma et al. PHYSICS IN MEDICINE AND BIOLOGY
- Radiomics in nuclear medicine: robustness, reproducibility, standardization, and how to avoid data analysis traps and replication crisis
- (2019) Alex Zwanenburg EUROPEAN JOURNAL OF NUCLEAR MEDICINE AND MOLECULAR IMAGING
- Radiomic feature stability across 4D respiratory phases and its impact on lung tumor prognosis prediction
- (2019) Qian Du et al. PLoS One
- Assessing radiomic feature robustness to interpolation in 18F-FDG PET imaging
- (2019) Philip Whybra et al. Scientific Reports
- Radiation Necrosis and White Matter Lesions in Pediatric Patients With Brain Tumors Treated With Pencil Beam Scanning Proton Therapy
- (2018) Beat Bojaxhiu et al. INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS
- Repeatability and reproducibility of radiomic features: A systematic review
- (2018) Alberto Traverso et al. INTERNATIONAL JOURNAL OF RADIATION ONCOLOGY BIOLOGY PHYSICS
- Texture analysis of 3D dose distributions for predictive modelling of toxicity rates in radiotherapy
- (2018) Linda Rossi et al. RADIOTHERAPY AND ONCOLOGY
- Towards a modular decision support system for radiomics: A case study on rectal cancer
- (2018) Roberto Gatta et al. ARTIFICIAL INTELLIGENCE IN MEDICINE
- What does research reproducibility mean?
- (2016) Steven N. Goodman et al. Science Translational Medicine
- Revisiting the Robustness of PET-Based Textural Features in the Context of Multi-Centric Trials
- (2016) Clément Bailly et al. PLoS One
- Impact of Reconstruction Algorithms on CT Radiomic Features of Pulmonary Tumors: Analysis of Intra- and Inter-Reader Variability and Inter-Reconstruction Algorithm Variability
- (2016) Hyungjin Kim et al. PLoS One
- Measuring Computed Tomography Scanner Variability of Radiomics Features
- (2015) Dennis Mackin et al. INVESTIGATIVE RADIOLOGY
- Radiomic feature clusters and Prognostic Signatures specific for Lung and Head & Neck cancer
- (2015) Chintan Parmar et al. Scientific Reports
- Robust Radiomics Feature Quantification Using Semiautomatic Volumetric Segmentation
- (2014) Chintan Parmar et al. PLoS One
- Method agreement analysis: A review of correct methodology
- (2010) P.F. Watson et al. THERIOGENOLOGY
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