![Loading...](https://link.springer.com/static/c4a417b97a76cc2980e3c25e2271af3129e08bbe/images/pdf-preview/spacer.gif)
-
Article
Non-local spatially varying finite mixture models for image segmentation
In this work, we propose a new Bayesian model for unsupervised image segmentation based on a combination of the spatially varying finite mixture models (SVFMMs) and the non-local means (NLM) framework. The pro...
-
Chapter and Conference Paper
ONCOhabitats Glioma Segmentation Model
ONCOhabitats is an open online service that provides a fully automatic analysis of tumor vascular heterogeneity in gliomas based on multiparametric MRI. Having a model capable of accurately segment pathologica...
-
Chapter and Conference Paper
An Online Platform for the Automatic Reporting of Multi-parametric Tissue Signatures: A Case Study in Glioblastoma
Glioblastomas are infiltrative and deeply invasive neoplasms characterized by high vascular proliferation and diffuse margins. As a consequence, this lesion presents a high degree of heterogeneity that require...
-
Article
Probabilistic change detection and visualization methods for the assessment of temporal stability in biomedical data quality
Knowledge discovery on biomedical data can be based on on-line, data-stream analyses, or using retrospective, timestamped, off-line datasets. In both cases, changes in the processes that generate data or in th...
-
Article
HealthAgents: distributed multi-agent brain tumor diagnosis and prognosis
We present an agent-based distributed decision support system for the diagnosis and prognosis of brain tumors developed by the HealthAgents project. HealthAgents is a European Union funded research project, whic...
-
Chapter and Conference Paper
Genomics and Metabolomics Research for Brain Tumour Diagnosis Based on Machine Learning
The incorporation of new biomedical technologies in the diagnosis and prognosis of cancer is changing medicine to an evidence-based diagnosis. We summarize some studies related to brain tumour research in Euro...