A review on recent developments in cancer detection using Machine Learning and Deep Learning models
Cancer is a fatal illness frequently caused by a variety of obsessive changes and genetic
disorders. Cancer cells knowing as abnormal cells can grow in any part of the human body …
disorders. Cancer cells knowing as abnormal cells can grow in any part of the human body …
PatchResNet: multiple patch division–based deep feature fusion framework for brain tumor classification using MRI images
Modern computer vision algorithms are based on convolutional neural networks (CNNs),
and both end-to-end learning and transfer learning modes have been used with CNN for …
and both end-to-end learning and transfer learning modes have been used with CNN for …
Role of ensemble deep learning for brain tumor classification in multiple magnetic resonance imaging sequence data
The biopsy is a gold standard method for tumor grading. However, due to its invasive nature,
it has sometimes proved fatal for brain tumor patients. As a result, a non-invasive computer …
it has sometimes proved fatal for brain tumor patients. As a result, a non-invasive computer …
Applications of artificial intelligence in magnetic resonance imaging of primary pediatric cancers: a scoping review and CLAIM score assessment
B Tsang, A Gupta, MS Takahashi, H Baffi, T Ola… - Japanese Journal of …, 2023 - Springer
Purposes To review the uses of AI for magnetic resonance (MR) imaging assessment of
primary pediatric cancer and identify common literature topics and knowledge gaps. To …
primary pediatric cancer and identify common literature topics and knowledge gaps. To …
Ai enabled accident detection and alert system using iot and deep learning for smart cities
As the number of vehicles increases, road accidents are on the rise every day. According to
the World Health Organization (WHO) survey, 1.4 million people have died, and 50 million …
the World Health Organization (WHO) survey, 1.4 million people have died, and 50 million …
BrainGAN: brain MRI image generation and classification framework using GAN architectures and CNN models
HHN Alrashedy, AF Almansour, DM Ibrahim… - Sensors, 2022 - mdpi.com
Deep learning models have been used in several domains, however, adjusting is still
required to be applied in sensitive areas such as medical imaging. As the use of technology …
required to be applied in sensitive areas such as medical imaging. As the use of technology …
Crossover smell agent optimized multilayer perceptron for precise brain tumor classification on MRI images
M Arumugam, A Thiyagarajan, L Adhi… - Expert Systems with …, 2024 - Elsevier
The Brain tumor is considered an unusual growth of cells in the nervous system that restricts
the normal functionality of the brain. However, is generated in the skull and pressures the …
the normal functionality of the brain. However, is generated in the skull and pressures the …
Smart brain tumor diagnosis system utilizing deep convolutional neural networks
Y Anagun - Multimedia Tools and Applications, 2023 - Springer
The early diagnosis of cancer is crucial to provide prompt and adequate management of the
diseases. Imaging tests, in particular magnetic resonance imaging (MRI), are the first …
diseases. Imaging tests, in particular magnetic resonance imaging (MRI), are the first …
[Retracted] Cyclic GAN Model to Classify Breast Cancer Data for Pathological Healthcare Task
An algorithm framework based on CycleGAN and an upgraded dual‐path network (DPN) is
suggested to address the difficulties of uneven staining in pathological pictures and difficulty …
suggested to address the difficulties of uneven staining in pathological pictures and difficulty …
Vision transformer outperforms deep convolutional neural network-based model in classifying X-ray images
The standard approach for automated clinical image diagnosis is being held with the use of
Convolutional Neural Networks (CNN) for a decade. Vision Transformers (ViT) are new in …
Convolutional Neural Networks (CNN) for a decade. Vision Transformers (ViT) are new in …