Artificial Intelligence for biological heterogeneity assessment of glioblastoma based on medical image analysis
Improving patient prognosis, predicting response to treatment
Magnetic Resonance Image Preprocessing
MRI quality improvement by supressing unwilling distortions and artifacts such as magnetic field inhomogeneities, image noise, patient motion, etc.
accessAnatomical Tumor Segmentation
Automated delineation of enhancing tumor, necrotic core and peritumoral edema tissues through Deep Learning state-of-the-art Convolutional Neural Networks.
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Imaging Biomarker Quantification
Functional assessment of biological imaging markers from perfusion and diffusion magnetic resonance sequences.
accessMultiparametric Tissue Signature
Heterogeneity assessment of the tumor by means of the detection of functional habitats within the lesion through state-of-the-art unsupervised machine learning analysis.
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PROCESSED CASES
USERS
INSTITUTIONS
Clinical trial services
Efficient patient stratification based on advanced imaging biomarkers can save up to 10% in a drug development cost in a clinical trial.
Technology patented P201431289
Artificial Intelligence technology to transform complex multi-parametric imaging data into clinically interpretable information.
Functional Habitats
The multiparametric tissue signature automatically captures the tumor heterogeneity, providing a set of functional habitats with high prognostic capabilities.
ONCOhabitats technology
Open-access services for tumor heterogeneity assessment, implementing consolidated state-of-the-art techniques.
