Cargando…

Reproducibility of CT-based radiomic features against image resampling and perturbations for tumour and healthy kidney in renal cancer patients

Computed Tomography (CT) is widely used in oncology for morphological evaluation and diagnosis, commonly through visual assessments, often exploiting semi-automatic tools as well. Well-established automatic methods for quantitative imaging offer the opportunity to enrich the radiologist interpretati...

Descripción completa

Detalles Bibliográficos
Autores principales:	Mottola, Margherita, Ursprung, Stephan, Rundo, Leonardo, Sanchez, Lorena Escudero, Klatte, Tobias, Mendichovszky, Iosif, Stewart, Grant D, Sala, Evis, Bevilacqua, Alessandro
Formato:	Online Artículo Texto
Lenguaje:	English
Publicado:	Nature Publishing Group UK 2021
Materias:	Article
Acceso en línea:	https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8172898/ https://www.ncbi.nlm.nih.gov/pubmed/34078993 http://dx.doi.org/10.1038/s41598-021-90985-y

Ejemplares similares

Feasibility and sensitivity study of radiomic features in photoacoustic imaging of patient-derived xenografts
por: Escudero Sanchez, Lorena, et al.
Publicado: (2022)

Publisher Correction: Feasibility and sensitivity study of radiomic features in photoacoustic imaging of patient-derived xenografts
por: Escudero Sanchez, Lorena, et al.
Publicado: (2022)

Robustness of radiomic features in CT images with different slice thickness, comparing liver tumour and muscle
por: Escudero Sanchez, Lorena, et al.
Publicado: (2021)

Radiomics of computed tomography and magnetic resonance imaging in renal cell carcinoma—a systematic review and meta-analysis
por: Ursprung, Stephan, et al.
Publicado: (2020)

Tissue-specific and interpretable sub-segmentation of whole tumour burden on CT images by unsupervised fuzzy clustering
por: Rundo, Leonardo, et al.
Publicado: (2020)

Ultrasound-guided targeted biopsies of CT-based radiomic tumour habitats: technical development and initial experience in metastatic ovarian cancer
por: Beer, Lucian, et al.
Publicado: (2020)

MRI-derived radiomics model for baseline prediction of prostate cancer progression on active surveillance
por: Sushentsev, Nikita, et al.
Publicado: (2021)

Impact of GAN-based lesion-focused medical image super-resolution on the robustness of radiomic features
por: de Farias, Erick Costa, et al.
Publicado: (2021)

Comparative performance of MRI-derived PRECISE scores and delta-radiomics models for the prediction of prostate cancer progression in patients on active surveillance
por: Sushentsev, Nikita, et al.
Publicado: (2021)

Lesion-specific 3D-printed moulds for image-guided tissue multi-sampling of ovarian tumours: A prospective pilot study
por: Delgado-Ortet, Maria, et al.
Publicado: (2023)

Clinically Interpretable Radiomics-Based Prediction of Histopathologic Response to Neoadjuvant Chemotherapy in High-Grade Serous Ovarian Carcinoma
por: Rundo, Leonardo, et al.
Publicado: (2022)

Three-Dimensional Printed Molds for Image-Guided Surgical Biopsies: An Open Source Computational Platform
por: Crispin-Ortuzar, Mireia, et al.
Publicado: (2020)

Serial changes in tumour measurements and apparent diffusion coefficients in prostate cancer patients on active surveillance with and without histopathological progression
por: Sushentsev, Nikita, et al.
Publicado: (2022)

Time series radiomics for the prediction of prostate cancer progression in patients on active surveillance
por: Sushentsev, Nikita, et al.
Publicado: (2023)

Focus U-Net: A novel dual attention-gated CNN for polyp segmentation during colonoscopy
por: Yeung, Michael, et al.
Publicado: (2021)

Unified Focal loss: Generalising Dice and cross entropy-based losses to handle class imbalanced medical image segmentation
por: Yeung, Michael, et al.
Publicado: (2022)

The Impact of Resampling and Denoising Deep Learning Algorithms on Radiomics in Brain Metastases MRI
por: Moummad, Ilyass, et al.
Publicado: (2021)

The Primacy of High B-Value 3T-DWI Radiomics in the Prediction of Clinically Significant Prostate Cancer
por: Bevilacqua, Alessandro, et al.
Publicado: (2021)

Radiomic Signatures Associated with CD8(+) Tumour-Infiltrating Lymphocytes: A Systematic Review and Quality Assessment Study
por: Ramlee, Syafiq, et al.
Publicado: (2022)

Fingerprint resampling: A generic method for efficient resampling
por: Mestdagh, Merijn, et al.
Publicado: (2015)

A Low-Dose CT-Based Radiomic Model to Improve Characterization and Screening Recall Intervals of Indeterminate Prevalent Pulmonary Nodules
por: Rundo, Leonardo, et al.
Publicado: (2021)

Integrative radiogenomics for virtual biopsy and treatment monitoring in ovarian cancer
por: Martin-Gonzalez, Paula, et al.
Publicado: (2020)

Minimizing acquisition-related radiomics variability by image resampling and batch effect correction to allow for large-scale data analysis
por: Ligero, Marta, et al.
Publicado: (2020)

Calibrating the Dice Loss to Handle Neural Network Overconfidence for Biomedical Image Segmentation
por: Yeung, Michael, et al.
Publicado: (2022)

Correlating Radiomic Features of Heterogeneity on CT with Circulating Tumor DNA in Metastatic Melanoma
por: Gill, Andrew B., et al.
Publicado: (2020)

Robustness of magnetic resonance radiomic features to pixel size resampling and interpolation in patients with cervical cancer
por: Park, Shin-Hyung, et al.
Publicado: (2021)

Comparative performance of fully-automated and semi-automated artificial intelligence methods for the detection of clinically significant prostate cancer on MRI: a systematic review
por: Sushentsev, Nikita, et al.
Publicado: (2022)

AutoRadiomics: A Framework for Reproducible Radiomics Research
por: Woznicki, Piotr, et al.
Publicado: (2022)

Image resampling and discretization effect on the estimate of myocardial radiomic features from T1 and T2 mapping in hypertrophic cardiomyopathy
por: Marfisi, Daniela, et al.
Publicado: (2022)

Resampling methods : a practical guide to data analysis /
por: Good, Phillip I.
Publicado: (2001)

Resampling methods : a practical guide to data analysis
por: Good, Phillip I.
Publicado: (1999)

Precision radiogenomics: fusion biopsies to target tumour habitats in vivo
por: Crispin-Ortuzar, Mireia, et al.
Publicado: (2021)

Resampling methods for dependent data
por: Lahiri, S N
Publicado: (2003)

Resampling methods for dependent data /
por: Lahiri, S. N. (Soumendra Nath)
Publicado: (2003)

Mathematical statistics with resampling and R /
por: Chihara, Laura, 1957-
Publicado: (2011)

Mathematical statistics with resampling and R
por: Chihara, Laura, et al.
Publicado: (2011)

Resampling-based methods for biologists
por: Fieberg, John R., et al.
Publicado: (2020)

Letter to the Editor on “Comparative performance of fully-automated and semi-automated artificial intelligence methods for the detection of clinically significant prostate cancer on MRI: a systematic review”
por: Bevilacqua, Alessandro, et al.
Publicado: (2023)

Spatial response resampling (SR(2)): Accounting for the spatial point spread function in hyperspectral image resampling
por: Inamdar, Deep, et al.
Publicado: (2023)

Radiomic and Volumetric Measurements as Clinical Trial Endpoints—A Comprehensive Review
por: Funingana, Ionut-Gabriel, et al.
Publicado: (2022)

Cannot write session to /tmp/vufind_sessions/sess_kt43jthvuq60mbi5vd52u534na