International Journal of Imaging Systems and Technology

Papers
(The H4-Index of International Journal of Imaging Systems and Technology is 27. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-11-01 to 2024-11-01.)
ArticleCitations
Automatic COVID‐19 CT segmentation using U‐Net integrated spatial and channel attention mechanism104
ME‐Net: Multi‐encoder net framework for brain tumor segmentation86
RETRACTED: Novel computer‐aided lung cancer detection based on convolutional neural network‐based and feature‐based classifiers using metaheuristics60
Future IoT tools for COVID‐19 contact tracing and prediction: A review of the state‐of‐the‐science58
Multimodal brain tumor detection and classification using deep saliency map and improved dragonfly optimization algorithm58
An intelligent fuzzy inference rule‐based expert recommendation system for predictive diabetes diagnosis57
Breast cancer histopathological image classification using attention high‐order deep network49
Convolutional capsule network for COVID‐19 detection using radiography images48
mRMR‐based hybrid convolutional neural network model for classification of Alzheimer's disease on brain magnetic resonance images41
Fusion of convolutional neural networks based on Dempster–Shafer theory for automatic pneumonia detection from chest X‐ray images41
Melanoma segmentation: A framework of improved DenseNet77 and UNET convolutional neural network40
Randomly initialized convolutional neural network for the recognition of COVID‐19 using X‐ray images37
Classification with respect to colon adenocarcinoma and colon benign tissue of colon histopathological images with a new CNN model: MA_ColonNET36
En‐ConvNet: A novel approach for glaucoma detection from color fundus images using ensemble of deep convolutional neural networks36
DHS‐CapsNet: Dual horizontal squash capsule networks for lung and colon cancer classification from whole slide histopathological images36
A comparative analysis of deep neural network architectures for the dynamic diagnosis of COVID‐19 based on acoustic cough features35
RETRACTED: Implementation of deep neural networks for classifying electroencephalogram signal using fractional S‐transform for epileptic seizure detection34
Detection and diagnosis of brain tumors using deep learning convolutional neural networks34
Deeply supervisedU‐Netfor mass segmentation in digital mammograms31
COLI‐Net: Deep learning‐assisted fully automated COVID‐19 lung and infection pneumonia lesion detection and segmentation from chest computed tomography images30
Three‐class classification of brain magnetic resonance images using average‐pooling convolutional neural network30
A deep learning approach for classification of COVID and pneumonia using DenseNet‐20130
Recognition of ischaemia and infection in diabetic foot ulcer: A deep convolutional neural network based approach29
A novel and efficient deep learning approach for COVID‐19 detection using X‐ray imaging modality28
Detecting brain tumors using deep learning convolutional neural network with transfer learning approach28
Comparison of the impacts of dermoscopy image augmentation methods on skin cancer classification and a new augmentation method with wavelet packets28
A novelmultimodalityanatomical image fusion method based on contrast and structure extraction27
Transfer learning‐based platform for detecting multi‐classification retinal disorders using optical coherence tomography images27
An accurate and noninvasive skin cancer screening based on imaging technique27
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