Publications from our Researchers

Several of our current PhD candidates and fellow researchers at the Data Science Institute have published, or in the proccess of publishing, papers to present their research.  

Citation

BibTex format

@inproceedings{Wang:2019,
author = {Wang, S and Dai, C and Mo, Y and Angelini, E and Guo, Y and Bai, W},
title = {Automatic Brain Tumour Segmentation and Biophysics-Guided Survival Prediction},
url = {http://arxiv.org/abs/1911.08483v1},
year = {2019}
}

RIS format (EndNote, RefMan)

TY  - CPAPER
AB - Gliomas are the most common malignant brain tumourswith intrinsicheterogeneity. Accurate segmentation of gliomas and theirsub-regions onmulti-parametric magnetic resonance images (mpMRI)is of great clinicalimportance, which defines tumour size, shape andappearance and providesabundant information for preoperative diag-nosis, treatment planning andsurvival prediction. Recent developmentson deep learning have significantlyimproved the performance of auto-mated medical image segmentation. In thispaper, we compare severalstate-of-the-art convolutional neural network modelsfor brain tumourimage segmentation. Based on the ensembled segmentation, wepresenta biophysics-guided prognostic model for patient overall survivalpredic-tion which outperforms a data-driven radiomics approach. Our methodwonthe second place of the MICCAI 2019 BraTS Challenge for theoverall survivalprediction.
AU - Wang,S
AU - Dai,C
AU - Mo,Y
AU - Angelini,E
AU - Guo,Y
AU - Bai,W
PY - 2019///
TI - Automatic Brain Tumour Segmentation and Biophysics-Guided Survival Prediction
UR - http://arxiv.org/abs/1911.08483v1
ER -