Vision transformer based classification of gliomas from histopathological images

E Goceri - Expert Systems with Applications, 2024 - Elsevier
Early and accurate detection and classification of glioma types is of paramount importance
in determining treatment planning and increasing the survival rate of patients. At present …

Enhancing brain tumor classification through ensemble attention mechanism

F Celik, K Celik, A Celik - Scientific Reports, 2024 - nature.com
Brain tumors pose a serious threat to public health, impacting thousands of individuals
directly or indirectly worldwide. Timely and accurate detection of these tumors is crucial for …

[HTML][HTML] An eXplainable deep learning model for multi-modal MRI grading of IDH-mutant astrocytomas

H Ayaz, O Oladimeji, I McLoughlin, D Tormey… - Results in …, 2024 - Elsevier
IDH-Mutant-astrocytomas are malignant brain glioma tumors. They are graded as lower
grade (grades 2 and 3) or higher grade (grade 4) according to their rate of growth and …

Brain tumor grade classification using the ConvNext architecture

Y Mehmood, UI Bajwa - Digital Health, 2024 - journals.sagepub.com
Objective Brain tumor grade is an important aspect of brain tumor diagnosis and helps to
plan for treatment. Traditional methods of diagnosis, including biopsy and manual …

Brain tumor classification for combining the advantages of multilayer dense net‐based feature extraction and hyper‐parameters tuned attentive dual residual …

S Anantharajan, S Gunasekaran… - NMR in …, 2024 - Wiley Online Library
In this manuscript, attentive dual residual generative adversarial network optimized using
wild horse optimization algorithm for brain tumor detection (ADRGAN‐WHOA‐BTD) is …

Nakagami-fuzzy imaging for grading brain tumors by analyzing fractal complexity

O Alpar - Applied Soft Computing, 2024 - Elsevier
Gliomas are the brain tumors in glial cells, which are categorized into four numerical grades,
I-II-III-IV, to quantize the aggressiveness and severity of the tumors; while divided into two …

Brain tumor grade classification using multi‐step pre‐training

Y Mehmood, UI Bajwa… - International Journal of …, 2024 - Wiley Online Library
Medical images offer a non‐invasive method to diagnose different diseases, but using them
manually produces unreliable results. Modern deep learning architectures and techniques …

Addressing challenges in accurate brain tumor classification in MRI: a transfer learning approach with EfficientNetB3 and comprehensive model evaluation

S Das, RS Goswami - Multimedia Tools and Applications, 2024 - Springer
Brain tumors pose significant health risks because of uncontrolled and abnormal cell growth,
potentially leading to the devastating of certain organs and even death, mostly in adult …

A Lightweight Multimodal Xception Network for Glioma Grading Using MRI Images

Y Liang, D Li, J Ren, W Gao… - International Journal of …, 2024 - Wiley Online Library
Gliomas are the most common type of primary brain tumors, classified into low‐grade
gliomas (LGGs) and high‐grade gliomas (HGGs). There is a significant difference in survival …

Brain Tumor Classification Through MR Imaging: A Comparative Analysis

G Prasanna Kumar, K Kiran, K Penmetsa… - … on Cognitive Computing …, 2023 - Springer
Tumor in brain is one of the serious diseases throughout the world and it leads to death
around 300 thousand people in 2020. Hence, Brain tumor diagnosis is a sensible and …