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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:

CT liver tumor segmentation hybrid approach using neutrosophic sets, fast fuzzy c-means and adaptive watershed algorithm
Ahmed M. Anter, Aboul Ella Hassenian
Artificial Intelligence in Medicine (2018) Vol. 97, pp. 105-117
Open Access | Times Cited: 96

Showing 1-25 of 96 citing articles:

Brain tumor detection based on Convolutional Neural Network with neutrosophic expert maximum fuzzy sure entropy
Fatih Özyurt, Eser Sert, Engin Avcı, et al.
Measurement (2019) Vol. 147, pp. 106830-106830
Closed Access | Times Cited: 237
Deep Learning With Radiomics for Disease Diagnosis and Treatment: Challenges and Potential
Xingping Zhang, Yanchun Zhang, Guijuan Zhang, et al.
Frontiers in Oncology (2022) Vol. 12
Open Access | Times Cited: 106
A lightweight neural network with multiscale feature enhancement for liver CT segmentation
Mohammed Yusuf Ansari, Yin Yang, Shidin Balakrishnan, et al.
Scientific Reports (2022) Vol. 12, Iss. 1
Open Access | Times Cited: 78
Eres-UNet++: Liver CT image segmentation based on high-efficiency channel attention and Res-UNet++
Jian Li, Kongyu Liu, Yating Hu, et al.
Computers in Biology and Medicine (2023) Vol. 158, pp. 106501-106501
Closed Access | Times Cited: 65
A hybrid deep segmentation network for fundus vessels via deep-learning framework
Lei Yang, Huaixin Wang, Qingshan Zeng, et al.
Neurocomputing (2021) Vol. 448, pp. 168-178
Closed Access | Times Cited: 98
X-Net: Multi-branch UNet-like network for liver and tumor segmentation from 3D abdominal CT scans
Jianning Chi, Xiaoying Han, Chengdong Wu, et al.
Neurocomputing (2021) Vol. 459, pp. 81-96
Closed Access | Times Cited: 56
A survey on the utilization of Superpixel image for clustering based image segmentation
Buddhadev Sasmal, Krishna Gopal Dhal
Multimedia Tools and Applications (2023) Vol. 82, Iss. 23, pp. 35493-35555
Open Access | Times Cited: 26
A Multiple Layer U-Net, Un-Net, for Liver and Liver Tumor Segmentation in CT
Song-Toan Tran, Ching-Hwa Cheng, Don‐Gey Liu
IEEE Access (2020) Vol. 9, pp. 3752-3764
Open Access | Times Cited: 67
Computer-aided diagnosis of liver lesions using CT images: A systematic review
P. Vaidehi Nayantara, Surekha Kamath, K. Manjunath, et al.
Computers in Biology and Medicine (2020) Vol. 127, pp. 104035-104035
Closed Access | Times Cited: 49
PA‐ResSeg: A phase attention residual network for liver tumor segmentation from multiphase CT images
Yingying Xu, Ming Cai, Lanfen Lin, et al.
Medical Physics (2021) Vol. 48, Iss. 7, pp. 3752-3766
Open Access | Times Cited: 46
Deep Federated Machine Learning-Based Optimization Methods for Liver Tumor Diagnosis: A Review
Ahmed M. Anter, Laith Abualigah
Archives of Computational Methods in Engineering (2023) Vol. 30, Iss. 5, pp. 3359-3378
Closed Access | Times Cited: 17
Lesion segmentation method for multiple types of liver cancer based on balanced dice loss
Jun Xie, Jiajun Zhou, Meiyi Yang, et al.
Medical Physics (2025)
Open Access
A Novel Bio-Inspired Deep Learning Approach for Liver Cancer Diagnosis
Rania M. Ghoniem
Information (2020) Vol. 11, Iss. 2, pp. 80-80
Open Access | Times Cited: 48
A Study of the Neutrosophic Set Significance on Deep Transfer Learning Models: an Experimental Case on a Limited COVID-19 Chest X-ray Dataset
Nour Eldeen M. Khalifa, Florentín Smarandache, Gunasekaran Manogaran, et al.
Cognitive Computation (2021) Vol. 16, Iss. 4, pp. 1602-1611
Open Access | Times Cited: 38
LDNNET: Towards Robust Classification of Lung Nodule and Cancer Using Lung Dense Neural Network
Ying Chen, Yerong Wang, Fei Hu, et al.
IEEE Access (2021) Vol. 9, pp. 50301-50320
Open Access | Times Cited: 33
Computer Vision Approach for Liver Tumor Classification Using CT Dataset
Mubasher Hussain, Najia Saher, Salman Qadri
Applied Artificial Intelligence (2022) Vol. 36, Iss. 1
Open Access | Times Cited: 22
CPAD-Net: Contextual parallel attention and dilated network for liver tumor segmentation
Xuehu Wang, Shuping Wang, Zhiling Zhang, et al.
Biomedical Signal Processing and Control (2022) Vol. 79, pp. 104258-104258
Closed Access | Times Cited: 22
Automated liver tissues delineation techniques: A systematic survey on machine learning current trends and future orientations
Ayman Al‐Kababji, Fayçal Bensaali, Sarada Prasad Dakua, et al.
Engineering Applications of Artificial Intelligence (2022) Vol. 117, pp. 105532-105532
Open Access | Times Cited: 22
Efficient Liver Segmentation using Advanced 3D-DCNN Algorithm on CT Images
S. Subha, U. Kumaran
Engineering Technology & Applied Science Research (2025) Vol. 15, Iss. 1, pp. 19324-19330
Open Access
Deep learning neural network for texture feature extraction in oral cancer: enhanced loss function
Bishal Bhandari, Abeer Alsadoon, P. W. C. Prasad, et al.
Multimedia Tools and Applications (2020) Vol. 79, Iss. 37-38, pp. 27867-27890
Closed Access | Times Cited: 37
A New Type of Fuzzy-Rule-Based System With Chaotic Swarm Intelligence for Multiclassification of Pain Perception From fMRI
Ahmed M. Anter, Gan Huang, Linling Li, et al.
IEEE Transactions on Fuzzy Systems (2020) Vol. 28, Iss. 6, pp. 1096-1109
Closed Access | Times Cited: 32
Texture appearance model, a new model-based segmentation paradigm, application on the segmentation of lung nodule in the CT scan of the chest
Faridoddin Shariaty, Mahdi Orooji, Elena Velichko, et al.
Computers in Biology and Medicine (2021) Vol. 140, pp. 105086-105086
Closed Access | Times Cited: 31
Semi-automatic liver tumor segmentation with adaptive region growing and graph cuts
Zhen Yang, Yuqian Zhao, Miao Liao, et al.
Biomedical Signal Processing and Control (2021) Vol. 68, pp. 102670-102670
Closed Access | Times Cited: 29
A diagnosis system by U-net and deep neural network enabled with optimal feature selection for liver tumor detection using CT images
Munipraveena Rela, Nagaraja Rao Suryakari, Ramana Reddy Patil
Multimedia Tools and Applications (2022) Vol. 82, Iss. 3, pp. 3185-3227
Closed Access | Times Cited: 21
Smart Low Level Laser Therapy System for Automatic Facial Dermatological Disorder Diagnosis
Duc Tri Phan, Quoc-Bao Ta, Cao Duong Ly, et al.
IEEE Journal of Biomedical and Health Informatics (2023) Vol. 27, Iss. 3, pp. 1546-1557
Closed Access | Times Cited: 11
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