Background and purpose Volume delineation is a well-recognised potential source of error
in radiotherapy. Whilst it is important to quantify the degree of interobserver variability (IOV) …

MRI is being increasingly used in oncology for staging, assessing tumour response and also
for treatment planning in radiotherapy. Both conformal and intensity-modulated radiotherapy …

Purpose Accurate segmentation of organs‐at‐risks (OAR s) is the key step for efficient
planning of radiation therapy for head and neck (HaN) cancer treatment. In the work, we …

In this paper we present a method to segment four brainstem structures (midbrain, pons,
medulla oblongata and superior cerebellar peduncle) from 3D brain MRI scans. The …

A novel atlas-based segmentation approach based on the combination of multiple
registrations is presented. Multiple atlases are registered to a target image. To obtain a …

We propose a new model to simulate the three-dimensional (3-D) growth of glioblastomas
multiforma (GBMs), the most aggressive glial tumors. The GBM speed of growth depends on …

Premature birth is a major and growing problem. Investigations into neuroanatomical
correlates and consequences of preterm birth are hampered by complex neonatal brain …

This paper presents a framework of a medical image analysis system for the brain tumor
segmentation and the brain tumor following-up over time using multi-spectral MRI images …

Simple Summary Artificial intelligence (AI) is the branch of computer science that enables
machines to learn, reason, and problem solve. In recent decades, AI has been developed …

Background Automated brain tumor segmentation methods are computational algorithms
that yield tumor delineation from, in this case, multimodal magnetic resonance imaging …