Elisa Scalco

Dottore di ricerca ed ingegnere biomedico, lavora come ricercatore presso ITB-CNR dal 2019. Ha ricevuto la laurea triennale nel 2007 e la laurea specialistica nel 2009, entrambe in ingegneria biomedica, presso il Politecnico di Milano. Nel 2014 ha ottenuto il titolo di dottore di ricerca in Tecnologie Biomediche presso l'Università degli Studi di Milano Bicocca discutendo una tesi dal titolo: "Evaluation of morphological and structural variations in parotid glands during radiotherapy in the head-and-neck district".

Sviluppo e applicazione di metodi per l'elaborazione e l'analisi di immagini biomediche, con particolare attenzione per la registrazione delle immagini, l'estrazione di indici quantitativi da immagini CT e MRI (radiomica). Il principale campo di applicazione riguarda il settore oncologico per la diagnosi e classificazione dei tumori e la predizione della risposta al trattamento per tumore e organi a rischio.

A novel bayesian approach with conditional autoregressive specification for intravoxel incoherent motion diffusion-weighted MRI

T2w-MRI signal normalization affects radiomics features reproducibility.

Multi-steps registration protocol for multimodal MR images of hip skeletal muscles in a longitudinal study

A new Probabilistic Active Contour region-based method for multiclass medical image segmentation.

The mHealth

Triggered intravoxel incoherent motion MRI for the assessment of calf muscle perfusion during isometric intermittent exercise.

Texture Analysis of T1-w and T2-w MR Images Allows a Quantitative Evaluation of Radiation-Induced Changes of Internal Obturator Muscles after Radiotherapy for Prostate Cancer.

Early prediction of radiotherapy-induced parotid shrinkage and toxicity based on CT radiomics and fuzzy classification.

A Comparative Evaluation of 3 Different Free-Form Deformable Image Registration and Contour Propagation Methods for Head and Neck MRI: The Case of Parotid Changes During Radiotherapy

Texture analysis of medical images for radiotherapy applications.

A Comparative Evaluation of 3 Different Free-Form Deformable Image Registration and Contour Propagation Methods for Head and Neck MRI.

Characterization of cervical lymph-nodes using a multi-parametric and multi-modal approach for an early prediction of tumor response to chemo-radiotherapy.

Evaluation of different CT lung anatomies for proton therapy with pencil beam scanning delivery, using a validated non-rigid image registration method.

Early classification of parotid glands shrinkage in radiotherapy patients: A comparative study

Assessment and clinical validation of margins for adaptive simultaneous integrated boost in neo-adjuvant radiochemotherapy for rectal cancer.

Likelihood-fuzzy analysis of parotid gland shrinkage in radiotherapy patients

The Shape of Parotid DVH Predicts the Entity of Gland Deformation During IMRT for Head and Neck Cancers.

Multimodal non-rigid registration methods based on local variability measures in computed tomography and magnetic resonance brain images

Early changes of parotid density and volume predict modifications at the end of therapy and intensity of acute xerostomia.

Texture analysis for the assessment of structural changes in parotid glands induced by radiotherapy

Texture analysis for the assessment of structural changes in parotid glands induced by radiotherapy

Density variation of parotid glands during IMRT for head-neck cancer: Correlation with treatment and anatomical parameters

Comparative high resolution pQCT analysis of femoral neck indicates different bone mass distribution in osteoporosis and osteoarthritis

Quantitative parameters of parotid deformation are highly correlated to DVH: evidence of a dose-beath effect around 15GY

Image-based dose-volume effects prediction

An automatic contour propagation method to follow parotid glands deformation during head-and-neck cancer Tomotherapy.

Elastic Registration Based on Particle Filter in Radiotherapy Images with Brain Deformations.