We provide a method to extract the tractographic features from structural MR images for patients with brain tumor

The purpose of this project is to be able to automatically and efficiently segment and classify high-grade and low-grade gliomas.

Pathomics Research Projects

NiftyNet-based implementation of Autofocus Net and Autofocus Layer.

NiftyNet-based implementation of the Autofocus Layer for semantic segmentation.

Use of state of the art Convolutional neural network architectures including 3D UNet, 3D VNet and 2D UNets for Brain Tumor Segmentation and using segmented image features for Survival Prediction of patients through deep neural networks.

Exploring the Information Content of Glioma Differentiation using SDEs

An implementation of Mask R-CNN algorithm to perform automatic object detection, localization, classification and instance segmentation of immunoreactive tumor cells on Ki-67 stained glioma images.

TensorFlow Version of AMF-Net for glioma grading and the classification of meningiomas and gliomas

Code for deep learning-based glioma/tumor growth models

This repo is for segmentation of T2 hyp regions in gliomas.

In this project, we created a convolutional neural network using the EfficientNetB1 model in Keras to perform Image Classification of MRI brain scans with reasonably high (97.4%) accuracy.

IRIS-MRS-AI is a tool that classifies IDH and TERTp mutations in gliomas. Besides these capabilities, IRIS-MRS-AI is a tool that can create custom models using users' data.

APOLLO is an Accurate and independently validated Prediction mOdel of Lower-grade gLiomas Overall survival

Glioblastoma multiforme (GBM) biomarker knowledge base

This repository contains Matlab codes developed for the thesis of the exam of Mathematical Models for Biomedicine, a.y. 2022-23, Master of Science in Mathematical Engineering at Politecnico di Torino, held by proff. Chiara Giverso, Luigi Preziosi, Luca Mesin. This work had been developed in cooperation with Lorenzo Vito Dal Zovo and Enrico Ortu.

IDH Classification for Gliomas using CNN and Transformers.

🤗 HuggingFace space for Raidionics 🤗

🤗 neukit: web application for automatic brain extraction and preoperative tumor segmentation from MRI

Nondestructive Spatial Lipidomics for Glioma Classification - Tissue Similarity and Grading