A multi-metric registration strategy for the alignment of longitudinal brain images in pediatric oncology
Survival of pediatric patients with brain tumor has increased over the past 20 years, and increasing evidence of iatrogenic toxicities has been reported.... Leggi tutto.
SLEEP-SEE-THROUGH: Explainable Deep Learning for Sleep Event Detection and Quantification From Wearable Somnography
Evidence is rapidly accumulating that multifactorial nocturnal monitoring, through the coupling of wearable devices and deep learning, may be disruptive for early... Leggi tutto.
Development of a multiomics database for personalized prognostic forecasting in head and neck cancer: The Big Data to Decide EU Project
Despite advances in treatments, 30% to 50% of stage III-IV head and neck squamous cell carcinoma (HNSCC) patients relapse within 2 years after treatment. The Big... Leggi tutto.
Baseline MRI-Radiomics Can Predict Overall Survival in Non-Endemic EBV-Related Nasopharyngeal Carcinoma Patients
Advanced stage nasopharyngeal cancer (NPC) shows highly variable treatment outcomes, suggesting the need for independent prognostic factors.... Leggi tutto.
Methodology and technology for the development of a prognostic MRI-based radiomic model for the outcome of head and neck cancer patients
The purpose of this study was to establish a methodology and technology for the development of an MRI-based radiomic signature for prognosis of overall survival... Leggi tutto.
Prognostic role of pre-treatment magnetic resonance imaging (MRI) radiomic analysis in patients with squamous cell carcinoma of the head and neck (SCCHN).
Emerging data suggest that radiomics can be used to predict outcomes in SCCHN. At present, only few data are available for pre-treatment MRI.... Leggi tutto.
Radiomic features for patients with primary soft tissue sarcomas: A prognostic study
Prognosis of extremity soft tissue sarcomas (ESTS) and retroperitoneal sarcomas (RPS) is currently estimated on clinical-pathological features, as those incorporated... Leggi tutto.
Relevance of apparent diffusion coefficient features for a radiomics-based prediction of response to induction chemotherapy in sinonasal cancer
In this paper, several radiomics-based predictive models of response to induction chemotherapy (IC) in sinonasal cancers (SNCs) are built and tested. Models were... Leggi tutto.
Technical Note: Virtual phantom analyses for preprocessing evaluation and detection of a robust feature set for MRI-radiomics of the brain
The purpose of the paper was to use a virtual phantom to identify a set of radiomic features from T1-weighted and T2-weighted magnetic resonance imaging (MRI) of... Leggi tutto.
Assessment of the effect of intensity standardization on the reliability of T1-weighted MRI radiomic features: experiment on a virtual phantom
The effect of time of repetition (TR) and time of echo (TE) on radiomic features was evaluated using a virtual phantom. Forty-two T1-weighted MRI images of the same... Leggi tutto.