Deformable image registration is a fundamental task in medical image processing. Among
its most important applications, one may cite: 1) multi-modality fusion, where information …

Central nervous system (CNS) tumors come with vastly heterogeneous histologic,
molecular, and radiographic landscapes, rendering their precise characterization …

This paper provides an overview of medical robotics, from the perspective of a researcher
who has been actively involved in the field for 17 years. Like all robot systems, medical …

Glioblastoma (GBM) is a highly invasive brain tumor, whose cells infiltrate surrounding
normal brain tissue beyond the lesion outlines visible in the current medical scans. These …

We present a framework for modeling gliomas growth and their mechanical impact on the
surrounding brain tissue (the so-called, mass-effect). We employ an Eulerian continuum …

Reaction-diffusion based tumor growth models have been widely used in the literature for
modeling the growth of brain gliomas. Lately, recent models have started integrating medical …

Obtaining validation data and comparison metrics for segmentation of magnetic resonance
images (MRI) are difficult tasks due to the lack of reliable ground truth. This problem is even …

Brain lesion segmentation provides a valuable tool for clinical diagnosis and research, and
convolutional neural networks (CNNs) have achieved unprecedented success in the …

Radiotherapy for brain glioma treatment relies on magnetic resonance (MR) and computed
tomography (CT) images. These images provide information on the spatial extent of the …

This paper investigates the problem of atlas registration of brain images with gliomas.
Multiparametric imaging modalities (T1, T1-CE, T2, and FLAIR) are first utilized for …