AI‐enhanced detection of clinically relevant structural and functional anomalies in MRI: Traversing the landscape of conventional to explainable approaches
P Khosravi, S Mohammadi, F Zahiri… - Journal of Magnetic …, 2024 - Wiley Online Library
Anomaly detection in medical imaging, particularly within the realm of magnetic resonance
imaging (MRI), stands as a vital area of research with far‐reaching implications across …
imaging (MRI), stands as a vital area of research with far‐reaching implications across …
Optimizing the topology of convolutional neural network (CNN) and artificial neural network (ANN) for brain tumor diagnosis (BTD) through MRIs
The use of MRI analysis for BTD and tumor type detection has considerable importance
within the domain of machine vision. Numerous methodologies have been proposed to …
within the domain of machine vision. Numerous methodologies have been proposed to …
[HTML][HTML] Develo** a Comprehensive Oil Spill Detection Model for Marine Environments
Detecting oil spills in marine environments is crucial for avoiding environmental damage
and facilitating rapid response efforts. In this study, we propose a robust method for oil spill …
and facilitating rapid response efforts. In this study, we propose a robust method for oil spill …
Deep learning approaches for brain tumor detection and classification using mri images (2020 to 2024): A systematic review
Brain tumor is a type of disease caused by uncontrolled cell proliferation in the brain leading
to serious health issues such as memory loss and motor impairment. Therefore, early …
to serious health issues such as memory loss and motor impairment. Therefore, early …
Brain tumor detection and classification in MRI using hybrid ViT and GRU model with explainable AI in Southern Bangladesh
Brain tumor, a leading cause of uncontrolled cell growth in the central nervous system,
presents substantial challenges in medical diagnosis and treatment. Early and accurate …
presents substantial challenges in medical diagnosis and treatment. Early and accurate …
Advancing Brain Tumor Detection: A Thorough Investigation of CNNs, Clustering, and SoftMax Classification in the Analysis of MRI Images
Brain tumors pose a significant global health challenge due to their high prevalence and
mortality rates across all age groups. Detecting brain tumors at an early stage is crucial for …
mortality rates across all age groups. Detecting brain tumors at an early stage is crucial for …
Improving brain tumor classification: an approach integrating pre-trained CNN models and machine learning algorithms
Accurate detection of brain tumors is crucial for enhancing patient outcomes, yet the
interpretation of Magnetic Resonance Imaging (MRI) scans poses significant challenges …
interpretation of Magnetic Resonance Imaging (MRI) scans poses significant challenges …
Enhanced MRI-based brain tumour classification with a novel Pix2pix generative adversarial network augmentation framework
The scarcity of medical imaging datasets and privacy concerns pose significant challenges
in artificial intelligence-based disease prediction. This poses major concerns to patient …
in artificial intelligence-based disease prediction. This poses major concerns to patient …
Explainable Lightweight Block Attention Module Framework for Network-Based IoT Attack Detection
In the rapidly evolving landscape of internet usage, ensuring robust cybersecurity measures
has become a paramount concern across diverse fields. Among the numerous cyber threats …
has become a paramount concern across diverse fields. Among the numerous cyber threats …
Optimizing smart home intrusion detection with harmony-enhanced extra trees
In this study, we present an innovative network intrusion detection system (IDS) tailored for
Internet of Things (IoT)-based smart home environments, offering a novel deployment …
Internet of Things (IoT)-based smart home environments, offering a novel deployment …