Perfusion maps extraction (EUCAIM-SW-054_T-02-01-002)

https://bio.tools/perfusion_maps_extraction

This tool extracts perfusion maps from dynamic imaging data (e.g., DCE-MRI) using pharmacokinetic models or semi-quantitative methods. It supports the evaluation of blood flow and tissue vascularity.

Sourced from

  • bio.toolsperfusion_maps_extraction

Related resources

A machine learning-based tool to estimate the overall survival probability in patients with neuroblastoma, supporting clinical decision-making and prognosis.

A machine learning model that predicts overall survival in patients with glioblastoma, using radiomic and clinical features.

Performs volumetric analysis of brain structures by segmenting and calculating the volume of grey matter, white matter, and CSF. Results support studies on neurodegeneration, development, or disease progression.

Extracts deep features from MR images using pretrained neural networks. These features can be used for classification, clustering, or survival prediction tasks in medical imaging.

Computes R1 and T1 maps from MR images, showing the rate and time of longitudinal relaxation. These are key quantitative biomarkers for tissue characterization.

Extracts diffusion-related maps (e.g., ADC, IVIM, Kurtosis) from DWI sequences to evaluate microstructural properties of tissues, commonly used in oncology and neurology.