A survey on cancer detection via convolutional neural networks: Current challenges and future directions

P Sharma, DR Nayak, BK Balabantaray, M Tanveer… - Neural Networks, 2024 - Elsevier
Cancer is a condition in which abnormal cells uncontrollably split and damage the body
tissues. Hence, detecting cancer at an early stage is highly essential. Currently, medical …

[HTML][HTML] Vision transformers in multi-modal brain tumor MRI segmentation: A review

P Wang, Q Yang, Z He, Y Yuan - Meta-Radiology, 2023 - Elsevier
Brain tumors have shown extreme mortality and increasing incidence during recent years,
which bring enormous challenges for the timely diagnosis and effective treatment of brain …

Brain tumor analysis using deep learning and VGG-16 ensembling learning approaches

A Younis, L Qiang, CO Nyatega, MJ Adamu… - Applied Sciences, 2022 - mdpi.com
A brain tumor is a distorted tissue wherein cells replicate rapidly and indefinitely, with no
control over tumor growth. Deep learning has been argued to have the potential to …

Brain tumor detection based on deep learning approaches and magnetic resonance imaging

AB Abdusalomov, M Mukhiddinov, TK Whangbo - Cancers, 2023 - mdpi.com
Simple Summary In this research, we addressed the challenging task of brain tumor
detection in MRI scans using a large collection of brain tumor images. We demonstrated that …

A deep analysis of brain tumor detection from mr images using deep learning networks

MI Mahmud, M Mamun, A Abdelgawad - Algorithms, 2023 - mdpi.com
Creating machines that behave and work in a way similar to humans is the objective of
artificial intelligence (AI). In addition to pattern recognition, planning, and problem-solving …

Metaheuristics optimization-based ensemble of deep neural networks for Mpox disease detection

S Asif, M Zhao, F Tang, Y Zhu, B Zhao - Neural Networks, 2023 - Elsevier
The rising number of cases of human Mpox has emerged as a major global concern due to
the daily increase of cases in several countries. The disease presents various skin …

Brain tumor segmentation and classification on MRI via deep hybrid representation learning

N Farajzadeh, N Sadeghzadeh… - Expert Systems with …, 2023 - Elsevier
Detecting brain tumors plays an important role in patients' lives as it can help specialists
save them or let them succumb to a terminal illness otherwise. Magnetic Resonance …

[HTML][HTML] Advance brain tumor segmentation using feature fusion methods with deep U-Net model with CNN for MRI data

AH Nizamani, Z Chen, AA Nizamani… - Journal of King Saud …, 2023 - Elsevier
In modern healthcare, the precision of medical image segmentation holds immense
significance for diagnosis and treatment planning. Deep learning techniques, such as …

Combining CNN features with voting classifiers for optimizing performance of brain tumor classification

N Alturki, M Umer, A Ishaq, N Abuzinadah… - Cancers, 2023 - mdpi.com
Simple Summary This study presents a hybrid model for brain tumor detection. Contrary to
manual featur extraction, features extracted from a convolutional neural network are used to …

Review of medical image processing using quantum-enabled algorithms

F Yan, H Huang, W Pedrycz, K Hirota - Artificial Intelligence Review, 2024 - Springer
Efficient and reliable storage, analysis, and transmission of medical images are imperative
for accurate diagnosis, treatment, and management of various diseases. Since quantum …