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OpenAlex Citation Counts

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OpenAlex is a bibliographic catalogue of scientific papers, authors and institutions accessible in open access mode, named after the Library of Alexandria. It's citation coverage is excellent and I hope you will find utility in this listing of citing articles!

If you click the article title, you'll navigate to the article, as listed in CrossRef. If you click the Open Access links, you'll navigate to the "best Open Access location". Clicking the citation count will open this listing for that article. Lastly at the bottom of the page, you'll find basic pagination options.

Requested Article:

Automated pathological brain detection system: A fast discrete curvelet transform and probabilistic neural network based approach
Deepak Ranjan Nayak, Ratnakar Dash, Banshidhar Majhi, et al.
Expert Systems with Applications (2017) Vol. 88, pp. 152-164
Closed Access | Times Cited: 50

Showing 1-25 of 50 citing articles:

Convolutional neural network with batch normalization for glioma and stroke lesion detection using MRI
Javeria Amin, Muhammad Sharif, Muhammad Almas Anjum, et al.
Cognitive Systems Research (2019) Vol. 59, pp. 304-311
Closed Access | Times Cited: 78
A survey on cancer detection via convolutional neural networks: Current challenges and future directions
Pallabi Sharma, Deepak Ranjan Nayak, Bunil Kumar Balabantaray, et al.
Neural Networks (2023) Vol. 169, pp. 637-659
Closed Access | Times Cited: 31
Discrete ripplet-II transform and modified PSO based improved evolutionary extreme learning machine for pathological brain detection
Deepak Ranjan Nayak, Ratnakar Dash, Banshidhar Majhi
Neurocomputing (2017) Vol. 282, pp. 232-247
Closed Access | Times Cited: 65
Fast discrete curvelet transform and modified PSO based improved evolutionary extreme learning machine for breast cancer detection
Debendra Muduli, Ratnakar Dash, Banshidhar Majhi
Biomedical Signal Processing and Control (2021) Vol. 70, pp. 102919-102919
Closed Access | Times Cited: 49
Combining extreme learning machine with modified sine cosine algorithm for detection of pathological brain
Deepak Ranjan Nayak, Ratnakar Dash, Banshidhar Majhi, et al.
Computers & Electrical Engineering (2018) Vol. 68, pp. 366-380
Closed Access | Times Cited: 49
Classification of colorectal cancer based on the association of multidimensional and multiresolution features
Matheus Ribeiro, Leandro Alves Neves, Marcelo Zanchetta do Nascimento, et al.
Expert Systems with Applications (2018) Vol. 120, pp. 262-278
Closed Access | Times Cited: 45
Deep extreme learning machine with leaky rectified linear unit for multiclass classification of pathological brain images
Deepak Ranjan Nayak, Dibyasundar Das, Ratnakar Dash, et al.
Multimedia Tools and Applications (2019) Vol. 79, Iss. 21-22, pp. 15381-15396
Closed Access | Times Cited: 42
Multi-channeled MR brain image segmentation: A novel double optimization approach combined with clustering technique for tumor identification and tissue segmentation
Anitha Narayanan, M. Pallikonda Rajasekaran, Yudong Zhang, et al.
Journal of Applied Biomedicine (2018) Vol. 39, Iss. 2, pp. 350-381
Closed Access | Times Cited: 32
Brain pathology identification using computer aided diagnostic tool: A systematic review
Anjan Gudigar, U. Raghavendra, Ajay Hegde, et al.
Computer Methods and Programs in Biomedicine (2019) Vol. 187, pp. 105205-105205
Closed Access | Times Cited: 30
A Five-Level Wavelet Decomposition and Dimensional Reduction Approach for Feature Extraction and Classification of MR and CT Scan Images
Varun Srivastava, Ravindra Kumar Purwar
Applied Computational Intelligence and Soft Computing (2017) Vol. 2017, pp. 1-9
Open Access | Times Cited: 26
Automated Diagnosis of Pathological Brain Using Fast Curvelet Entropy Features
Deepak Ranjan Nayak, Ratnakar Dash, Xiaojun Chang, et al.
IEEE Transactions on Sustainable Computing (2018) Vol. 5, Iss. 3, pp. 416-427
Closed Access | Times Cited: 25
Application of fast curvelet Tsallis entropy and kernel random vector functional link network for automated detection of multiclass brain abnormalities
Deepak Ranjan Nayak, Ratnakar Dash, Banshidhar Majhi, et al.
Computerized Medical Imaging and Graphics (2019) Vol. 77, pp. 101656-101656
Closed Access | Times Cited: 25
An image classification framework exploring the capabilities of extreme learning machines and artificial bee colony
A. V. Reddy, Ch. Phani Krishna, Pradeep Kumar Mallick
Neural Computing and Applications (2019) Vol. 32, Iss. 8, pp. 3079-3099
Closed Access | Times Cited: 24
Classification of breast and colorectal tumors based on percolation of color normalized images
Guilherme Freire Roberto, Marcelo Zanchetta do Nascimento, Alessandro S. Martins, et al.
Computers & Graphics (2019) Vol. 84, pp. 134-143
Closed Access | Times Cited: 24
Development of pathological brain detection system using Jaya optimized improved extreme learning machine and orthogonal ripplet-II transform
Deepak Ranjan Nayak, Ratnakar Dash, Banshidhar Majhi
Multimedia Tools and Applications (2017) Vol. 77, Iss. 17, pp. 22705-22733
Closed Access | Times Cited: 22
MJaya-ELM: A Jaya algorithm with mutation and extreme learning machine based approach for sensorineural hearing loss detection
Deepak Ranjan Nayak, Yudong Zhang, Dibyasundar Das, et al.
Applied Soft Computing (2019) Vol. 83, pp. 105626-105626
Open Access | Times Cited: 20
Segmentation Method of Deterministic Feature Clustering for Identification of Brain Tumor Using MRI
Khurram Ejaz, Norhaida Mohd Suaib, Mohammad Shahid Kamal, et al.
IEEE Access (2023) Vol. 11, pp. 39695-39712
Open Access | Times Cited: 6
Automated quantification of ultrasonic fatty liver texture based on curvelet transform and SVD
R Bharath, Pradeep Kumar Mishra, P. Rajalakshmi
Journal of Applied Biomedicine (2017) Vol. 38, Iss. 1, pp. 145-157
Closed Access | Times Cited: 20
An automated computer-aided diagnosis system for classification of MR images using texture features and gbest-guided gravitational search algorithm
Ravi Shanker, Mahua Bhattacharya
Journal of Applied Biomedicine (2020) Vol. 40, Iss. 2, pp. 815-835
Closed Access | Times Cited: 17
An Improved Pathological Brain Detection System Based on Two-Dimensional PCA and Evolutionary Extreme Learning Machine
Deepak Ranjan Nayak, Ratnakar Dash, Banshidhar Majhi
Journal of Medical Systems (2017) Vol. 42, Iss. 1
Closed Access | Times Cited: 15
Stokes Space Modulation Format Identification for Optical Signals Using Probabilistic Neural Network
Ming Hao, Lianshan Yan, Anlin Yi, et al.
IEEE photonics journal (2018) Vol. 10, Iss. 3, pp. 1-13
Open Access | Times Cited: 15
An MRI brain disease classification system using PDFB-CT and GLCM with kernel-SVM for medical decision support
Yubraj Gupta, Ramesh Kumar Lama, Sang‐Woong Lee, et al.
Multimedia Tools and Applications (2020) Vol. 79, Iss. 43-44, pp. 32195-32224
Closed Access | Times Cited: 13
Review on Hybrid Segmentation Methods for Identification of Brain Tumor in MRI
Khurram Ejaz, Mohd Shafry Mohd Rahim, Muhammad Arif, et al.
Contrast Media & Molecular Imaging (2022) Vol. 2022, Iss. 1
Open Access | Times Cited: 8
Automated Detection and Classification of Meningioma Tumor from MR Images Using Sea Lion Optimization and Deep Learning Models
Aswathy Sukumaran, Ajith Abraham
Axioms (2021) Vol. 11, Iss. 1, pp. 15-15
Open Access | Times Cited: 11
A computer-aided diagnosis of multiple sclerosis based on mfVEP recordings
Luis de Santiago, Eva María Sánchez‐Morla, Miguel Ortiz del Castillo, et al.
PLoS ONE (2019) Vol. 14, Iss. 4, pp. e0214662-e0214662
Open Access | Times Cited: 11
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