A Deep Convolutional Neural Network for Pneumonia Detection in X-ray Images with Attention Ensemble
In the domain of AI-driven healthcare, deep learning models have markedly advanced
pneumonia diagnosis through X-ray image analysis, thus indicating a significant stride in the …
pneumonia diagnosis through X-ray image analysis, thus indicating a significant stride in the …
Enhancing pneumonia segmentation in lung radiographs: a jellyfish search optimizer approach
Segmentation of pneumonia on lung radiographs is vital for the precise diagnosis and
monitoring of the disease. It enables healthcare professionals to locate and quantify the …
monitoring of the disease. It enables healthcare professionals to locate and quantify the …
Unsupervised generative learning-based decision-making system for COVID-19 detection
Purpose The study aims to develop an unsupervised framework using COVGANs to learn
better visual representations of COVID-19 from unlabeled X-ray and CT scans. Methods We …
better visual representations of COVID-19 from unlabeled X-ray and CT scans. Methods We …
TL-LFF Net: transfer learning based lighter, faster, and frozen network for the detection of multi-scale mixed intracranial hemorrhages through genetic optimization …
Computed tomography (CT) is the most commonly used imaging method in intracranial
hemorrhage (ICH). Although deep learning (DL) models are well suited for detecting and …
hemorrhage (ICH). Although deep learning (DL) models are well suited for detecting and …
Unveiling Lung Diseases in CT Scan Images With a Hybrid Bio‐Inspired Mutated Spider‐Monkey and Crow Search Algorithm
Bio‐inspired computer‐aided diagnosis (CAD) has garnered significant attention in recent
years due to the inherent advantages of bio‐inspired evolutionary algorithms (EAs) in …
years due to the inherent advantages of bio‐inspired evolutionary algorithms (EAs) in …
Deep Learning Algorithms for Pneumonia: A Comparative Approach to Classification and Segmentation
VK Mishra, M Mishra, R Tiwari… - 2024 IEEE 6th …, 2024 - ieeexplore.ieee.org
The study compares the outcomes of numerous modern CNN architectures, such as ResNet-
50, VGG-16, and DenseNet-121, with conventional machine learning classifiers in order to …
50, VGG-16, and DenseNet-121, with conventional machine learning classifiers in order to …