Tumor heterogeneity is a well-known prognostic factor in head and neck squamous cell carcinoma (HNSCC). A major limitation of tissue- and blood-derived tumor markers is the lack of spatial resolution to image tumor heterogeneity. Tissue markers derived from tumor biopsies usually represent only a small tumor subregion at a single timepoint and are therefore often not representative of the tumors' biology or the biological alterations during and after treatment. Similarly, liquid biopsies give an overall picture of the tumors' secreted factors but completely lack any spatial resolution. Radiomics has the potential to give complete three-dimensional information about the tumor. We conducted a comprehensive literature search to assess the corr...
Introduction In this study, we investigate the role of radiomics for prediction of overall survival ...
Human cancers exhibit strong phenotypic differences that can be visualized noninvasively by medical ...
Baseline clinical prognostic factors for recurrent and/or metastatic (RM) head and neck squamous cel...
Tumor heterogeneity is a well-known prognostic factor in head and neck squamous cell carcinoma (HNSC...
Recent advances in machine learning and artificial intelligence technology have ensured automated ev...
Radiomics supposes an alternative non-invasive tumor characterization tool, which has experienced in...
Objectives Head and neck squamous cell carcinoma (HNSCC) shows a remarkable heterogeneity between tu...
BackgroundRadiomics has been widely investigated for non-invasive acquisition of quantitative textur...
Quantitative extraction of high-dimensional mineable data from medical images is a process known as ...
Objectives: To explore prognostic and predictive value of radiomics in patients with locally advance...
Purpose Radiomics has already been proposed as a prognostic biomarker in head and neck cancer (HN...
Current radiomic studies of head and neck squamous cell carcinomas (HNSCC) are typically based on da...
International audienceMedical image processing and analysis (also known as Radiomics) is arapidly gr...
Introduction In this study, we investigate the role of radiomics for prediction of overall survival ...
Human cancers exhibit strong phenotypic differences that can be visualized noninvasively by medical ...
Baseline clinical prognostic factors for recurrent and/or metastatic (RM) head and neck squamous cel...
Tumor heterogeneity is a well-known prognostic factor in head and neck squamous cell carcinoma (HNSC...
Recent advances in machine learning and artificial intelligence technology have ensured automated ev...
Radiomics supposes an alternative non-invasive tumor characterization tool, which has experienced in...
Objectives Head and neck squamous cell carcinoma (HNSCC) shows a remarkable heterogeneity between tu...
BackgroundRadiomics has been widely investigated for non-invasive acquisition of quantitative textur...
Quantitative extraction of high-dimensional mineable data from medical images is a process known as ...
Objectives: To explore prognostic and predictive value of radiomics in patients with locally advance...
Purpose Radiomics has already been proposed as a prognostic biomarker in head and neck cancer (HN...
Current radiomic studies of head and neck squamous cell carcinomas (HNSCC) are typically based on da...
International audienceMedical image processing and analysis (also known as Radiomics) is arapidly gr...
Introduction In this study, we investigate the role of radiomics for prediction of overall survival ...
Human cancers exhibit strong phenotypic differences that can be visualized noninvasively by medical ...
Baseline clinical prognostic factors for recurrent and/or metastatic (RM) head and neck squamous cel...