Brain Tumor Segmentation and Survival Prediction using 3D Attention UNet

Autor:	Islam, Mobarakol, VS, Vibashan, Jose, V Jeya Maria, Wijethilake, Navodini, Utkarsh, Uppal, Ren, Hongliang
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 work, we develop an attention convolutional neural network (CNN) to segment brain tumors from Magnetic Resonance Images (MRI). Further, we predict the survival rate using various machine learning methods. We adopt a 3D UNet architecture and integrate channel and spatial attention with the decoder network to perform segmentation. For survival prediction, we extract some novel radiomic features based on geometry, location, the shape of the segmented tumor and combine them with clinical information to estimate the survival duration for each patient. We also perform extensive experiments to show the effect of each feature for overall survival (OS) prediction. The experimental results infer that radiomic features such as histogram, location, and shape of the necrosis region and clinical features like age are the most critical parameters to estimate the OS. Comment: MICCAI-BrainLes Workshop
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2104.00985 Zobrazit plný text záznamu View this record from Arxiv