Evangelia I. Zacharaki

TL;DR: A computer‐assisted classification method combining conventional MRI and perfusion MRI is developed and used for differential diagnosis and consists of several steps including region‐of‐interest definition, feature extraction, feature selection, and classification.

TL;DR: This Review addresses the critical issues to ensure the proper development of radiomics as a biomarker and facilitate its implementation in clinical practice.

TL;DR: This multiparametric tissue characterization approach has potential applications in treatment, aiding computer-assisted surgery by determining the spatial distributions of healthy and neoplastic tissue, as well as in identifying tissue that is relatively more prone to tumor recurrence.

TL;DR: Validation on simulated and real images shows that the proposed registration framework, referred to as ORBIT (optimization of tumor parameters and registration of brain images with tumors), outperforms other available registration methods particularly for the regions close to the tumor, and it has the potential to assist in constructing statistical atlases from tumor-diseased brain images.

TL;DR: An approach to deformable registration of three-dimensional brain tumor images to a normal brain atlas indicates significant reduction in the registration error due to the presented approach as compared to the direct use of deformable image registration.