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 …
in determining treatment planning and increasing the survival rate of patients. At present …
Enhancing brain tumor classification through ensemble attention mechanism
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 …
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
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 …
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
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 …
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 …
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 …
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
Medical images offer a non‐invasive method to diagnose different diseases, but using them
manually produces unreliable results. Modern deep learning architectures and techniques …
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
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 …
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 …
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 …
around 300 thousand people in 2020. Hence, Brain tumor diagnosis is a sensible and …