Prediction of MGMT Methylation Status of Glioblastoma using Radiomics and Latent Space Shape Features

Autor:	Pálsson, Sveinn, Cerri, Stefano, Van Leemput, Koen
Rok vydání:	2021
Předmět:	Electrical Engineering and Systems Science - Image and Video Processing Computer Science - Computer Vision and Pattern Recognition
Druh dokumentu:	Working Paper
Popis:	In this paper we propose a method for predicting the status of MGMT promoter methylation in high-grade gliomas. From the available MR images, we segment the tumor using deep convolutional neural networks and extract both radiomic features and shape features learned by a variational autoencoder. We implemented a standard machine learning workflow to obtain predictions, consisting of feature selection followed by training of a random forest classification model. We trained and evaluated our method on the RSNA-ASNR-MICCAI BraTS 2021 challenge dataset and submitted our predictions to the challenge.
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2109.12339 Zobrazit plný text záznamu View this record from Arxiv