U-Net Based Glioblastoma Segmentation with Patient’s Overall Survival Prediction

2020 ◽  
pp. 22-32
Author(s):  
Asra Rafi ◽  
Junaid Ali ◽  
Tahir Akram ◽  
Kiran Fiaz ◽  
Ahmad Raza Shahid ◽  
...  
Keyword(s):  
Overall Survival ◽  
Survival Prediction ◽  
Overall Survival Prediction

scholarly journals miR-199a-3p and miR-214-3p improve the overall survival prediction of muscle-invasive bladder cancer patients after radical cystectomy

2017 ◽  
Vol 6 (10) ◽  
pp. 2252-2262 ◽  
Author(s):  
Thorsten H. Ecke ◽  
Katja Stier ◽  
Sabine Weickmann ◽  
Zhongwei Zhao ◽  
Laura Buckendahl ◽  
...  
Keyword(s):  
Overall Survival ◽  
Bladder Cancer ◽  
Cancer Patients ◽  
Radical Cystectomy ◽  
Invasive Bladder Cancer ◽  
Survival Prediction ◽  
Muscle Invasive Bladder Cancer ◽  
Muscle Invasive ◽  
Overall Survival Prediction

scholarly journals A Survey and Analysis on Automated Glioma Brain Tumor Segmentation and Overall Patient Survival Prediction

2021 ◽  
Author(s):  
Rupal Agravat ◽  
Mehul Raval
Keyword(s):  
Overall Survival ◽  
Brain Tumor ◽  
Automatic Segmentation ◽  
High Volume ◽  
Physical Symptoms ◽  
Tumor Segmentation ◽  
Survival Prediction ◽  
Neural Network Models ◽  
Brain Tumor Segmentation ◽  
Overall Survival Prediction

<div>Glioma is the most deadly brain tumor with high mortality. Treatment planning by human experts depends on the proper diagnosis of physical symptoms along with Magnetic Resonance(MR) image analysis. Highly variability of a brain tumor in terms of size, shape, location, and a high volume of MR images makes the analysis time-consuming. Automatic segmentation methods achieve a reduction in time with excellent reproducible results.</div><div>The article aims to survey the advancement of automated methods for Glioma brain tumor segmentation. It is also essential to make an objective evaluation of various models based on the benchmark. Therefore, the 2012 - 2019 BraTS challenges database evaluates state-of-the-art methods. The complexity of tasks under the challenge has grown from segmentation (Task1) to overall survival prediction (Task 2) to uncertainty prediction for classification (Task 3). The paper covers the complete gamut of brain tumor segmentation using handcrafted features to deep neural network models for Task 1. The aim is to showcase a complete change of trends in automated brain tumor models. The paper also covers end to end joint models involving brain tumor segmentation and overall survival prediction. All the methods are probed, and parameters that affect performance are tabulated and analyzed.</div>

PO-1187 Overall survival prediction in NSCLC: a radiomic approach with a multi-VOI analysis

2021 ◽  
Vol 161 ◽  
pp. S985
Author(s):  
S. Silipigni ◽  
M. Miele ◽  
S. Gentile ◽  
E. Molfese ◽  
P. Soda ◽  
...  
Keyword(s):  
Overall Survival ◽  
Survival Prediction ◽  
Overall Survival Prediction

scholarly journals Nomogram based overall survival prediction in stereotactic body radiotherapy for oligo-metastatic lung disease

2017 ◽  
Vol 123 (2) ◽  
pp. 182-188 ◽  
Author(s):  
S. Tanadini-Lang ◽  
J. Rieber ◽  
A.R. Filippi ◽  
M.M. Fode ◽  
J. Streblow ◽  
...  
Keyword(s):  
Overall Survival ◽  
Lung Disease ◽  
Stereotactic Body Radiotherapy ◽  
Survival Prediction ◽  
Metastatic Lung ◽  
Overall Survival Prediction
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