brain tumor
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2022 ◽  
Vol 73 ◽  
pp. 103438
Author(s):  
Weijin Xu ◽  
Huihua Yang ◽  
Mingying Zhang ◽  
Zhiwei Cao ◽  
Xipeng Pan ◽  
...  

2022 ◽  
Vol 22 (1) ◽  
pp. 1-30
Author(s):  
Rahul Kumar ◽  
Ankur Gupta ◽  
Harkirat Singh Arora ◽  
Balasubramanian Raman

Brain tumors are one of the critical malignant neurological cancers with the highest number of deaths and injuries worldwide. They are categorized into two major classes, high-grade glioma (HGG) and low-grade glioma (LGG), with HGG being more aggressive and malignant, whereas LGG tumors are less aggressive, but if left untreated, they get converted to HGG. Thus, the classification of brain tumors into the corresponding grade is a crucial task, especially for making decisions related to treatment. Motivated by the importance of such critical threats to humans, we propose a novel framework for brain tumor classification using discrete wavelet transform-based fusion of MRI sequences and Radiomics feature extraction. We utilized the Brain Tumor Segmentation 2018 challenge training dataset for the performance evaluation of our approach, and we extract features from three regions of interest derived using a combination of several tumor regions. We used wrapper method-based feature selection techniques for selecting a significant set of features and utilize various machine learning classifiers, Random Forest, Decision Tree, and Extra Randomized Tree for training the model. For proper validation of our approach, we adopt the five-fold cross-validation technique. We achieved state-of-the-art performance considering several performance metrics, 〈 Acc , Sens , Spec , F1-score , MCC , AUC 〉 ≡ 〈 98.60%, 99.05%, 97.33%, 99.05%, 96.42%, 98.19% 〉, where Acc , Sens , Spec , F1-score , MCC , and AUC represents the accuracy, sensitivity, specificity, F1-score, Matthews correlation coefficient, and area-under-the-curve, respectively. We believe our proposed approach will play a crucial role in the planning of clinical treatment and guidelines before surgery.


2022 ◽  
Vol 73 ◽  
pp. 103442
Author(s):  
Yujian Liu ◽  
Jie Du ◽  
Chi-Man Vong ◽  
Guanghui Yue ◽  
Juan Yu ◽  
...  

2022 ◽  
Vol 76 ◽  
pp. 102078
Author(s):  
Pablo Monterroso ◽  
Kristin J. Moore ◽  
Jeannette M. Sample ◽  
Natali Sorajja ◽  
Allison Domingues ◽  
...  

2022 ◽  
Vol 72 ◽  
pp. 103356
Author(s):  
Coşku Öksüz ◽  
Oğuzhan Urhan ◽  
Mehmet Kemal Güllü

Author(s):  
Omid Reza Tamtaji ◽  
Maryam Derakhshan ◽  
Fatemeh Zahra Rashidi Noshabad ◽  
Javad Razaviyan ◽  
Razie Hadavi ◽  
...  

A major terrifying ailment afflicting the humans throughout the world is brain tumor, which causes a lot of mortality among pediatric and adult solid tumors. Several major barriers to the treatment and diagnosis of the brain tumors are the specific micro-environmental and cell-intrinsic features of neural tissues. Absence of the nutrients and hypoxia trigger the cells’ mortality in the core of the tumors of humans’ brains: however, type of the cells’ mortality, including apoptosis or necrosis, has been not found obviously. Current studies have emphasized the non-coding RNAs (ncRNAs) since their crucial impacts on carcinogenesis have been discovered. Several investigations suggest the essential contribution of such molecules in the development of brain tumors and the respective roles in apoptosis. Herein, we summarize the apoptosis-related non-coding RNAs in brain tumors.


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