Related references
Note: Only part of the references are listed.Elongation, flatness and compactness indices to characterise particle form
Vasileios Angelidakis et al.
POWDER TECHNOLOGY (2022)
Radiomics for precision medicine: Current challenges, future prospects, and the proposal of a new framework
A. Ibrahim et al.
METHODS (2021)
A Low-Dose CT-Based Radiomic Model to Improve Characterization and Screening Recall Intervals of Indeterminate Prevalent Pulmonary Nodules
Leonardo Rundo et al.
DIAGNOSTICS (2021)
PET/CT Radiomics in Lung Cancer: An Overview
Francesco Bianconi et al.
APPLIED SCIENCES-BASEL (2020)
Value of Shape and Texture Features from 18F-FDG PET/CT to Discriminate between Benign and Malignant Solitary Pulmonary Nodules: An Experimental Evaluation
Barbara Palumbo et al.
DIAGNOSTICS (2020)
Spiculation Sign Recognition in a Pulmonary Nodule Based on Spiking Neural P Systems
Shi Qiu et al.
BIOMED RESEARCH INTERNATIONAL (2020)
Quantitative Imaging features Improve Discrimination of Malignancy in Pulmonary nodules
Yoganand Balagurunathan et al.
SCIENTIFIC REPORTS (2019)
Radiomics in Pulmonary Lesion Imaging
Cameron Hassani et al.
AMERICAN JOURNAL OF ROENTGENOLOGY (2019)
The complexity of tumor shape, spiculatedness, correlates with tumor radiomic shape features
Elaine Johanna Limkin et al.
SCIENTIFIC REPORTS (2019)
Malignant-benign classification of pulmonary nodules based on random forest aided by clustering analysis
Wenhao Wu et al.
PHYSICS IN MEDICINE AND BIOLOGY (2019)
Evaluation of the solitary pulmonary nodule: size matters, but do not ignore the power of morphology
Annemie Snoeckx et al.
INSIGHTS INTO IMAGING (2018)
Guidelines for Management of Incidental Pulmonary Nodules Detected on CT Images: From the Fleischner Society 2017
Heber MacMahon et al.
RADIOLOGY (2017)
Technical Challenges in the Clinical Application of Radiomics
Faiq A. Shaikh et al.
JCO CLINICAL CANCER INFORMATICS (2017)
A Combination of Shape and Texture Features for Classification of Pulmonary Nodules in Lung CT Images
Ashis Kumar Dhara et al.
JOURNAL OF DIGITAL IMAGING (2016)
Radiomic phenotype features predict pathological response in non-small cell lung cancer
Thibaud P. Coroller et al.
RADIOTHERAPY AND ONCOLOGY (2016)
Radiomics applied to lung cancer: a review
Madeleine Scrivener et al.
TRANSLATIONAL CANCER RESEARCH (2016)
Quantitative Computed Tomographic Descriptors Associate Tumor Shape Complexity and Intratumor Heterogeneity with Prognosis in Lung Adenocarcinoma
Olya Grove et al.
PLOS ONE (2015)
scikit-image: image processing in Python
Stefan van der Walt et al.
PEERJ (2014)
The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository
Kenneth Clark et al.
JOURNAL OF DIGITAL IMAGING (2013)
Probability of Cancer in Pulmonary Nodules Detected on First Screening CT
Annette McWilliams et al.
NEW ENGLAND JOURNAL OF MEDICINE (2013)
Reduced Lung-Cancer Mortality with Low-Dose Computed Tomographic Screening
Denise R. Aberle et al.
NEW ENGLAND JOURNAL OF MEDICINE (2011)
Biostatistics primer: Part 2
Brian R. Overholser et al.
NUTRITION IN CLINICAL PRACTICE (2008)
Share Paper
