Utility of Brain Parcellation in Enhancing Brain Tumor Segmentation and Survival Prediction

Zhang，Yue1,2; Wu，Jiewei3; Huang，Weikai1; Chen，Yifan4; Wu，Ed X.2; Tang，Xiaoying1

10.1007/978-3-030-72084-1_35

2021

6th International MICCAI Brain-Lesion Workshop (BrainLes)

0302-9743

1611-3349

978-3-030-72083-4

LECT NOTES ARTIF INT

12658 LNCS

391-400

OCT 04, 2020

null,null,ELECTR NETWORK

GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND

SPRINGER INTERNATIONAL PUBLISHING AG

In this paper, we proposed a UNet-based brain tumor segmentation method and a linear model-based survival prediction method. The effectiveness of UNet has been validated in automatically segmenting brain tumors from multimodal magnetic resonance (MR) images. Rather than network architecture, we focused more on making use of additional information (brain parcellation), training and testing strategy (coarse-to-fine), and ensemble technique to improve the segmentation performance. We then developed a linear classification model for survival prediction. Different from previous studies that mainly employ features from brain tumor segmentation, we also extracted features from brain parcellation, which further improved the prediction accuracy. On the challenge testing dataset, the proposed approach yielded average Dice scores of 88.43%, 84.51%, and 78.93% for the whole tumor, tumor core, and enhancing tumor in the segmentation task and an overall accuracy of 0.533 in the survival prediction task.

Brain parcellation Brain tumor segmentation Survival prediction UNet

第一 ; 通讯

英语

EI ; CPCI-S

Computer Science ; Radiology, Nuclear Medicine & Medical Imaging

Computer Science, Artificial Intelligence ; Computer Science, Interdisciplinary Applications ; Radiology, Nuclear Medicine & Medical Imaging

WOS:000892566900035

20212310474428

Brain ; Forecasting ; Image segmentation ; Magnetic resonance ; Medical imaging ; Network architecture ; Statistical tests

Biomedical Engineering:461.1 ; Biological Materials and Tissue Engineering:461.2 ; Magnetism: Basic Concepts and Phenomena:701.2 ; Mathematical Statistics:922.2

2-s2.0-85107377927

Scopus

1.Department of Electrical and Electronic Engineering,Southern University of Science and Technology,Shenzhen,China
2.Department of Electrical and Electronic Engineering,The University of Hong Kong,Hong Kong
3.School of Electronics and Information Technology,Sun Yat-Sen University,Guangzhou,China
4.School of Life Science and Technology,University of Electronic Science and Technology,Chengdu,China

Zhang，Yue,Wu，Jiewei,Huang，Weikai,et al. Utility of Brain Parcellation in Enhancing Brain Tumor Segmentation and Survival Prediction[C]. GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND:SPRINGER INTERNATIONAL PUBLISHING AG,2021:391-400.