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ORCIDInternational Journal of Imaging Systems and Technology, Volume 32
Volume 32, Number 1, January 2022
- Mohamed L. Seghier
:
Ten simple rules for reporting machine learning methods implementation and evaluation on biomedical data. 5-11 - Isaac Shiri, Hossein Arabi, Yazdan Salimi, Amirhossein Sanaat, Azadeh Akhavanallaf, Ghasem Hajianfar, Dariush Askari, Shakiba Moradi, Zahra Mansouri, Masoumeh Pakbin, Saleh Sandoughdaran, Hamid Abdollahi, Amir Reza Radmard, Kiara Rezaei-Kalantari, Mostafa Ghelich Oghli, Habib Zaidi:
COLI-Net: Deep learning-assisted fully automated COVID-19 lung and infection pneumonia lesion detection and segmentation from chest computed tomography images. 12-25 - Emine Cengil, Ahmet Çinar:
The effect of deep feature concatenation in the classification problem: An approach on COVID-19 disease detection. 26-40 - Sheikh Rafiul Islam, Santi P. Maity, Ajoy Kumar Ray, Mrinal Mandal:
Deep learning on compressed sensing measurements in pneumonia detection. 41-54 - Safa Ben Atitallah, Maha Driss, Wadii Boulila, Henda Ben Ghézala:
Randomly initialized convolutional neural network for the recognition of COVID-19 using X-ray images. 55-73 - Yu Fu, Peng Xue, Peng Zhao, Ning Li, Zhuodong Xu, Huizhong Ji, Zhili Zhang, Wentao Cui, Enqing Dong:
3D multi-resolution deep learning model for diagnosis of multiple pathological types on pulmonary nodules. 74-87 - Shubham Dodia, Annappa Basava, Mahesh Padukudru Anand:
A novel receptive field-regularized V-net and nodule classification network for lung nodule detection. 88-101 - Nasrin Amini, Ahmad Shalbaf:
Automatic classification of severity of COVID-19 patients using texture feature and random forest based on computed tomography images. 102-110 - Prabhakar Agarwal, Sandeep Kumar:
Electroencephalography based imagined alphabets classification using spatial and time-domain features. 111-122 - Kwabena Adu, Yongbin Yu, Jingye Cai, Isaac Asare, Jennifer Quahin:
The influence of the activation function in a capsule network for brain tumor type classification. 123-143 - Bo Fu, Yuhan Dong, Shilin Fu, Yuanxin Mao, Dang N. H. Thanh:
Learning domain transfer for unsupervised magnetic resonance imaging restoration and edge enhancement. 144-154 - Muhammed Yildirim, Ahmet Çinar:
Classification with respect to colon adenocarcinoma and colon benign tissue of colon histopathological images with a new CNN model: MA_ColonNET. 155-162 - Junghyun Song, Dongchan Kim, Yeji Han, Jun-Young Chung:
Comparative analysis of the kernel types in generalized autocalibrating partially parallel acquisition algorithms for accelerated three-dimensional magnetic resonance spectroscopic imaging data. 163-177 - Yaru Wang, Shihong Yue, Jun Chen, Qi Li:
Conductivity characteristics of human lung tissues. 178-191 - Sujit Kumar Das, Pinki Roy, Arnab Kumar Mishra:
Recognition of ischaemia and infection in diabetic foot ulcer: A deep convolutional neural network based approach. 192-208 - Hui Huang, Xi'an Feng, Jionghui Jiang, Peiyu Chen, Suying Zhou:
Mask RCNN algorithm for nuclei detection on breast cancer histopathological images. 209-217 - Belal Ahmad, Mohd Usama, Tanvir Ahmad, Shabnam Khatoon, Chaudhary Maqbool Alam:
An ensemble model of convolution and recurrent neural network for skin disease classification. 218-229 - Deepa Natarajan, Esakkirajan Sankaralingam, Keerthiveena Balraj, Selvakumar Karuppusamy:
A deep learning framework for glaucoma detection based on robust optic disc segmentation and transfer learning. 230-250 - Ridhma, Manvjeet Kaur, Sanjeev Sofat, Devendra K. Chouhan, Mahesh Prakash:
Automated measurement of sulcus angle on axial knee magnetic resonance images. 251-265 - Ying Zou, Jianxin Zhang, Shan Huang, Bin Liu:
Breast cancer histopathological image classification using attention high-order deep network. 266-279 - Pallavi Asthana, Madasu Hanmandlu, Sharda Vashisth:
Classification of brain tumor from magnetic resonance images using probabilistic features and possibilistic Hanman-Shannon transform classifier. 280-294 - Yanyan Shi, Zhiwei Tian, Meng Wang, Zuguang Rao, Feng Fu:
Reconstruction of conductivity distribution with a compound variational strategy in electrical impedance tomography. 295-306 - Sadia Anjum, Lal Hussain, Mushtaq Ali, Monagi H. Alkinani, Wajid Aziz, Sabrina Gheller, Adeel Ahmed Abbasi, Ali Raza Marchal, Harshini Suresh, Tim Q. Duong:
Detecting brain tumors using deep learning convolutional neural network with transfer learning approach. 307-323 - Arbab Sufyan, Muhammad Imran, Syed Attique Shah, Hamayoun Shahwani, Arbab Abdul Wadood:
A novel multimodality anatomical image fusion method based on contrast and structure extraction. 324-342 - Yigit Ali Üncü, Gençay Sevim, Murat Canpolat:
Approaches to preclinical studies with heterogeneous breast phantom using reconstruction and three-dimensional image processing algorithms for diffuse optical imaging. 343-353 - Gunjan Rajput, Shashank Agrawal, Gopal Raut, Santosh Kumar Vishvakarma:
An accurate and noninvasive skin cancer screening based on imaging technique. 354-368 - Xiaoming Liu, Shaocheng Wang, Jun Cao, Ying Zhang, Man Wang:
Uncertainty-guided self-ensembling model for semi-supervised segmentation of multiclass retinal fluid in optical coherence tomography images. 369-386 - Lamiaa Abdel-Hamid:
TWEEC: Computer-aided glaucoma diagnosis from retinal images using deep learning techniques. 387-401 - Ashokkumar S. R, Anupallavi S, MohanBabu G, M. Premkumar, V. Jeevanantham:
Emotion identification by dynamic entropy and ensemble learning from electroencephalogram signals. 402-413
Volume 32, Number 2, March 2022
- Shamik Tiwari, Anurag Jain:
A lightweight capsule network architecture for detection of COVID-19 from lung CT scans. 419-434 - Mehmet Kalayci, Hakan Ayyildiz, Seda Arslan Tuncer, Pinar Gundogan Bozdag, Gulden Eser Karlidag:
Can laboratory parameters be an alternative to CT and RT-PCR in the diagnosis of COVID-19? A machine learning approach. 435-443 - Summrina Kanwal, Faiza Khan, Sultan Alamri, Kia Dashtipour, Mandar Gogate:
COVID-opt-aiNet: A clinical decision support system for COVID-19 detection. 444-461 - Arun Kumar, Rajendra Prasad Mahapatra:
Detection and diagnosis of COVID-19 infection in lungs images using deep learning techniques. 462-475 - Said Yacine Boulahia, Mohamed Akrem Benatia, Abderrahmane Bouzar:
Att2ResNet: A deep attention-based approach for melanoma skin cancer classification. 476-489 - Zhirong Yang, Wenchuan Zhang:
Preoperative planning for jugular-foramen tumors: Preparation of a three-dimensional surgical drawing. 490-500 - U. Raghavendra, Anjan Gudigar, Tejaswi N. Rao, V. Rajinikanth, Edward J. Ciaccio, Chai Hong Yeong, Suresh Chandra Satapathy, Filippo Molinari, U. Rajendra Acharya:
Feature-versus deep learning-based approaches for the automated detection of brain tumor with magnetic resonance images: A comparative study. 501-516 - Yesim Eroglu, Muhammed Yildirim, Ahmet Çinar:
mRMR-based hybrid convolutional neural network model for classification of Alzheimer's disease on brain magnetic resonance images. 517-527 - Ying Fang, He Huang, Weiji Yang, Xiaomei Xu, Weiwei Jiang, Xiaobo Lai:
Nonlocal convolutional block attention module VNet for gliomas automatic segmentation. 528-543 - Stalin Babu Gedela, S. N. Tirumala Rao, R. Rajeswara Rao:
Automated assessment for Alzheimer's disease diagnosis from MRI images: Meta-heuristic assisted deep learning model. 544-563 - Jayesh George Melekoodappattu, Anto Sahaya Dhas, Binil Kumar K., K. S. Adarsh:
Malignancy detection on mammograms by integrating modified convolutional neural network classifier and texture features. 564-574 - Mina Mirjalili, Reza Zomorrodi, Zafiris J. Daskalakis, Sean L. Hill, Tarek K. Rajji:
Individualized real-time prediction of working memory performance by classifying electroencephalography signals. 575-589 - Ashraf Abuelhaija, Gameel Saleh, Osama Nashwan, Samer Issa, Sanaa Salama:
Multi- and dual-tuned microstripline-based transmit/receive switch for 7-Tesla magnetic resonance imaging. 590-599 - Bindu Madhavi Tummala, Soubhagya Sankar Barpanda:
Liver tumor segmentation from computed tomography images using multiscale residual dilated encoder-decoder network. 600-613 - Sally M. Elghamrawy, Aboul Ella Hassanien, Athanasios V. Vasilakos:
Genetic-based adaptive momentum estimation for predicting mortality risk factors for COVID-19 patients using deep learning. 614-628 - Lingraj Dora, Sanjay Agrawal, Rutuparna Panda, Ajith Abraham:
An efficient multiclass classifier for classification of Alzheimer's disease/mild cognitive impairment/Normal subjects. 629-641 - Cherifa Nabila Chaoui, Abdelghani Ghomari, Boudjelal Meftah:
Edge and anomaly detection of brain magnetic resonance images in a distributed environment. 642-657 - Safa Ben Atitallah, Maha Driss, Wadii Boulila, Anis Koubaa, Henda Ben Ghézala:
Fusion of convolutional neural networks based on Dempster-Shafer theory for automatic pneumonia detection from chest X-ray images. 658-672 - Tomás Pohl, Marek Jakab, Wanda Benesova:
Interpretability of deep neural networks used for the diagnosis of Alzheimer's disease. 673-686 - Sasikanth Shanmugam, Srinivasa Rao Surampudi:
A method for detecting and classifying the tumor regions in brain MRI images using vector index filtering and ANFIS classification process. 687-696
Volume 32, Number 3, May 2022
- Mohamed L. Seghier:
Demystifying desk rejection: A call to action for our authors. 701-703
- Thiyagarajan Padmapriya, Kalaiselvi Thiruvenkadam, Venugopal Priyadharshini:
Multimodal covid network: Multimodal bespoke convolutional neural network architectures for COVID-19 detection from chest X-ray's and computerized tomography scans. 704-716 - Orkun Eroglu, Muhammed Yildirim:
Automatic detection of eardrum otoendoscopic images in patients with otitis media using hybrid-based deep models. 717-727 - Fan Liu, Dongxiao Li, Xinyu Jin, Wenyuan Qiu:
Accelerated brain tumor dynamic contrast-enhanced MRI using Adaptive Pharmaco-Kinetic Model Constrained method. 728-739 - Neven Saleh, Manal Abdel Wahed, Ahmed M. Salaheldin:
Transfer learning-based platform for detecting multi-classification retinal disorders using optical coherence tomography images. 740-752 - Rahul Paul:
Topological features in addition to radiomics signature predict 1p19q status and tumor grade in low-grade gliomas. 753-766 - Limei Su, Shenjiao Huang, Zhengyin Wang, Zhiqin Zhang, Huajiang Wei, Tongsheng Chen:
Whole slide cervical image classification based on convolutional neural network and random forest. 767-777 - Vidya K. Sudarshan, Reshma A. Ramachandra, Nicole Si Min Tan, Smit Ojha, Ru San Tan:
VEntNet: Hybrid deep convolutional neural network model for automated multi-class categorization of chest X-rays. 778-797 - Yaroub Elloumi:
Cataract grading method based on deep convolutional neural networks and stacking ensemble learning. 798-814 - Anisha Arulappan, Ajith Bosco Raj Thankaraj:
Liver tumor segmentation using a new asymmetrical dilated convolutional semantic segmentation network in CT images. 815-830 - Mengkun Wu, Hao Sun, Zhenhui Sun, Xin Guo, Lunhui Duan, Yinglun Tan, Rui Cui:
A machine learning-based method for automatic diagnosis of ankle fracture using X-ray images. 831-842 - Muruganantham Manickam, Siva Rathinavelayatham, Saravanan Prabakeran, Kannan Geetha, Varadharajan Indumathi, Thirumaaran Sethukarasi:
Pulmonary disease diagnosis using African vulture optimized weighted support vector machine approach. 843-856 - Shaoguo Cui, Mingjun Wei, Chang Liu, Jingfeng Jiang:
GAN-segNet: A deep generative adversarial segmentation network for brain tumor semantic segmentation. 857-868 - Krishnamoorthy Sashi Rekha, Suthanthira Amalraj Miruna Joe Amali:
Efficient feature subset selection and classification using levy flight-based cuckoo search optimization with parallel support vector machine for the breast cancer data. 869-881 - Saurabh Shrikant Athalye, Gaurav Vijay:
Taylor series-based deep belief network for automatic classification of diabetic retinopathy using retinal fundus images. 882-901 - Zeeshan Ahmed, Shahbaz Qamar Panhwar, Attiya Baqai, Fahim Aziz Umrani, Munawar Ahmed, Arbaaz Khan:
Deep learning based automated detection of intraretinal cystoid fluid. 902-917 - Antony Dennis Ananth, Chenniappan Palanisamy:
Extended and optimized deep convolutional neural network-based lung tumor identification in big data. 918-934 - Mamta Juneja, Saasha Joshi, Naveen Singla, Shaurya Ahuja, Sumindar Kaur Saini, Niharika Thakur, Prashant Jindal:
Denoising of computed tomography using bilateral median based autoencoder network. 935-955 - Xiaofang Zhang, Bin Zhang, Xiaomin Liu, Jie Dong, Shujun Zhao, Suxiao Li:
Accurate classification of nodules and non-nodules from computed tomography images based on radiomics and machine learning algorithms. 956-968 - Shanshan Liu, Ruo Hu, Jianfang Wu, Xizheng Zhang, Jun He, Huimin Zhao, Huajia Wang, Xiangjun Li:
Research on data classification and feature fusion method of cancer nuclei image based on deep learning. 969-981 - Kiran Fiaz, Tahir Mustafa Madni, Fozia Anwar, Uzair Iqbal Janjua, Asra Rafi, Mian Muhammad Naeem Abid, Nasira Sultana:
Brain tumor segmentation and multiview multiscale-based radiomic model for patient's overall survival prediction. 982-999 - Nalini Bodasingi, Balaji Narayanam, Bhaskara Rao Jammu:
Automatic diagnosis of pneumonia using backward elimination method based SVM and its hardware implementation. 1000-1014 - Adel Abdelli, Rachida Saouli, Khalifa Djemal, Imane Youkana:
Multiple instance learning for classifying histopathological images of the breast cancer using residual neural network. 1015-1029
Volume 32, Number 4, July 2022
- Hyunsu Jeong, Hyunwook Kim, Jiwon Yoon, Kyungsup Go, Jeonghwan Gwak:
OVASO: Integrated binary CNN models to classify COVID-19, pneumonia and healthy lung in X-ray images. 1035-1048 - Durga Prasad Mannepalli, Varsha Namdeo:
An effective detection of COVID-19 using adaptive dual-stage horse herd bidirectional long short-term memory framework. 1049-1067 - Sevim Cengiz, Muhammed Yildirim, Abdullah Bas, Esin Ozturk-Isik:
ORYX-MRSI: A fully-automated open-source software for proton magnetic resonance spectroscopic imaging data analysis. 1068-1083 - Kushangi Atrey, Bikesh Kumar Singh, Abhijit Roy, Narendra Kuber Bodhey:
Real-time automated segmentation of breast lesions using CNN-based deep learning paradigm: Investigation on mammogram and ultrasound. 1084-1100 - Gunjan Rajput, Shashank Agrawal, Kunika Naresh Biyani, Santosh Kumar Vishvakarma:
Early breast cancer diagnosis using cogent activation function-based deep learning implementation on screened mammograms. 1101-1118 - Yusong Shen, Chaoen Hu, Peng Zhang, Jie Tian, Hui Hui:
A novel software framework for magnetic particle imaging reconstruction. 1119-1132 - Donghyuk Kim, Taewoo Nam, Daniel Hernández, Kyoung-Nam Kim:
Design of rectangular coaxial slot antenna for ultra-high-field magnetic resonance imaging. 1133-1142 - Ranpreet Kaur, Hamid Gholam Hosseini, Roopak Sinha:
Skin lesion segmentation using an improved framework of encoder-decoder based convolutional neural network. 1143-1158 - Ferdi Ozbilgin, Çetin Kurnaz:
An alternative approach for determining the cholesterol level: Iris analysis. 1159-1171 - Venkatesh Gauri Shankar, Dilip Singh Sisodia, Preeti Chandrakar:
A novel discriminant feature selection-based mutual information extraction from MR brain images for Alzheimer's stages detection and prediction. 1172-1191 - Tojo Mathew, B. Ajith, Jyoti R. Kini, Jeny Rajan:
Deep learning-based automated mitosis detection in histopathology images for breast cancer grading. 1192-1208 - Arnab Kumar Mishra, Pinki Roy, Sivaji Bandyopadhyay, Sujit Kumar Das:
CR-SSL: A closely related self-supervised learning based approach for improving breast ultrasound tumor segmentation. 1209-1220 - Fan Zhang, Junhua Zhu, Pengyi Hao, Fuli Wu, Yuanna Zheng:
BDU-net: Toward accurate segmentation of dental image using border guidance and feature map distortion. 1221-1230 - Lokesh Singh, Rekh Ram Janghel, Satya Prakash Sahu:
A hybrid feature fusion strategy for early fusion and majority voting for late fusion towards melanocytic skin lesion detection. 1231-1250 - Kaniska Samanta, Soumya Chatterjee, Rohit Bose:
Neuromuscular disease detection based on feature extraction from time-frequency images of EMG signals employing robust hyperbolic Stockwell transform. 1251-1262 - Sreedhar Kollem, Katta Rama Linga Reddy, Duggirala Srinivasa Rao, Chintha Rajendra Prasad, V. Malathy, J. Ajayan, Deboraj Muchahary:
Image denoising for magnetic resonance imaging medical images using improved generalized cross-validation based on the diffusivity function. 1263-1285 - Hanyuan Miao, Xiaohong Zhou, Wei Wang, Weiliang Jiang, Tao Jin:
Improved sparse representation algorithm for optical coherence tomography images. 1286-1293 - Xiongfei Jiao, Juan Li, Zhilei Zhao, Benjamin Badami:
An all-inclusive computer-aided melanoma diagnosis based on soft computing. 1294-1306 - M. Roy Reena, P. M. Ameer:
Identification of white blood cells for the diagnosis of acute myeloid leukemia. 1307-1317 - Komal Jindal, Rahul Upadhyay, Hari Shankar Singh:
A novel EEG channel selection and classification methodology for multi-class motor imagery-based BCI system design. 1318-1337 - Tanvi Dovedi, Rahul Upadhyay, Vinay Kumar:
Hybrid time-reassigned multisynchrosqueezing transform-Picard-based automated electroencephalography artifact correction methodology for brain-computer interface applications. 1338-1356 - Vedant Shukla, Prasad Khandekar, Arti Khaparde:
Estimation of Nonhomogeneous Noise in 2D Magnetic Resonance Imaging. 1357-1372 - Palanigurupackiam Nagaraj, Perumalsamy Deepalakshmi:
An intelligent fuzzy inference rule-based expert recommendation system for predictive diabetes diagnosis. 1373-1396 - Manoj Kumar Naik, Rutuparna Panda, Leena Samantaray, Ajith Abraham:
A novel threshold score based multiclass segmentation technique for brain magnetic resonance images using adaptive opposition slime mold algorithm. 1397-1413 - Egambaram Thirumagal, Saruladha Krishnamurthy:
Lung cancer classification using exponential mean saturation linear unit activation function in various generative adversarial network models. 1414-1428
Volume 32, Number 5, September 2022
- Gurram Sunitha, Arunachalam Rajesh, Mohammed Abd-Elnaby, Mahmoud M. A. Eid, Ahmed Nabih Zaki Rashed:
A comparative analysis of deep neural network architectures for the dynamic diagnosis of COVID-19 based on acoustic cough features. 1433-1446 - Muzaffer Aslan:
CoviDetNet: A new COVID-19 diagnostic system based on deep features of chest x-ray. 1447-1463 - Sachin Kumar, Sourabh Shastri, Shilpa Mahajan, Kuljeet Singh, Surbhi Gupta, Rajneesh Rani, Neeraj Mohan, Vibhakar Mansotra:
LiteCovidNet: A lightweight deep neural network model for detection of COVID-19 using X-ray images. 1464-1480 - Hasan Polat:
A modified DeepLabV3+ based semantic segmentation of chest computed tomography images for COVID-19 lung infections. 1481-1495 - J. Sahaya Jeniba, Arulappan Milton:
A multilevel self-attention based segmentation and classification technique using Directional Hexagonal Mixed Pattern algorithm for lung nodule detection in thoracic CT image. 1496-1510 - Cong Chao Bian, Ning Cao, Minghe Mao:
CSDL-Net: An iterative network based on compressed sensing and deep learning. 1511-1520 - Samla Salim, Sarath R.:
An improved invasive weed optimization enabled Shepard convolutional neural network for classification of breast cancer. 1521-1534 - Onkar Thorat, Siddharth Salvi, Shrey Dedhia, Chetashri Bhadane, Deepika Dongre:
Domain adaptation and weight initialization of neural networks for diagnosing interstitial lung diseases. 1535-1547 - Murat Firat, Cem Çankaya, Ahmet Çinar, Taner Tuncer:
Automatic detection of keratoconus on Pentacam images using feature selection based on deep learning. 1548-1560 - Thirumarai Selvi Chandraraju, Amudha Jeyaprakash:
Categorization of breast masses based on deep belief network parameters optimized using chaotic krill herd optimization algorithm for frequent diagnosis of breast abnormalities. 1561-1576 - Shi-jie Wang, Hua-qing Liu, Tao Yang, Ming-quan Huang, Bowen Zheng, Tao Wu, Lan-qing Han, Yong Zhang, Jie Ren:
Machine learning based on automated breast volume scanner (ABVS) radiomics for differential diagnosis of benign and malignant BI-RADS 4 lesions. 1577-1587 - Xin Yang, Li Liu, Tao Li:
MR-UNet: An UNet model using multi-scale and residual convolutions for retinal vessel segmentation. 1588-1603 - Hongfei Wang, Ping Yang, Chuan Xu, Lei Min, Shuai Wang, Bing Xu:
Lung CT image enhancement based on total variational frame and wavelet transform. 1604-1614 - M. B. Bijoy, Sai Manoj Akondi, S. Abdul Fathaah, Akash Raut, P. N. Pournami, P. B. Jayaraj:
Cervix type detection using a self-supervision boosted object detection technique. 1615-1630 - Weisheng Li, Feifei Chao, Guofen Wang, Jun Fu, Xiuxiu Peng:
Medical image fusion based on local Laplacian decomposition and iterative joint filter. 1631-1645 - Özlem Polat, Zümray Dokur, Tamer Ölmez:
Brain tumor classification by using a novel convolutional neural network structure. 1646-1660 - Rania M. Abdelazeem, Omnia Hamdy:
Utilizing the spatial frequency domain imaging to investigate change in optical parameters of skin exposed to thermal-hydrotherapy: Ex-vivo study. 1661-1672 - Fatih Veysel Nurçin:
Improved segmentation of overlapping red blood cells on malaria blood smear images with TransUNet architecture. 1673-1680 - Chinnu Jacob, Gopakumar Chandrasekhara Menon:
Pathological categorization of lung carcinoma from multimodality images using convolutional neural networks. 1681-1695 - Nirmal Yadav:
A deep data-driven approach for enhanced segmentation of blood vessel for diabetic retinopathy. 1696-1708 - Geetha Pavani Pappu, Talabhakthula Krishna, Birendra Biswal, Prakash Kumar Karn, Pradyut Kumar Biswal, Shazia Hasan, Debasish Nayak:
A deeply supervised maximum response texton based SegNet for simultaneous multi retinal lesion segmentation. 1709-1726 - Zhili Zhang, Taohui Xiao, Yu Fu, Yuqiang Gao, Meirong Ren, Wentao Cui, Enqing Dong:
3D multi-resolution attention capsule network for diagnosing multi-pathological types of pulmonary nodules. 1727-1742 - Karishma Rao, Manu Bansal, Gagandeep Kaur:
An optimized morphology transform-based diagnostic computed tomography image enhancement using edge map. 1743-1760 - Mourtada Benazzouz, Mohammed Lamine Benomar, Youcef Moualek:
Modified U-Net for cytological medical image segmentation. 1761-1773 - Himanshu K. Gajera, Mukesh A. Zaveri, Deepak Ranjan Nayak:
Patch-based local deep feature extraction for automated skin cancer classification. 1774-1788 - Moye Yu, Yi Wang:
Intelligent detection and applied research on diabetic retinopathy based on the residual attention network. 1789-1800 - Pallavi Asthana, Madasu Hanmandlu, Sharda Vashisth:
Brain tumor detection and patient survival prediction using U-Net and regression model. 1801-1814
Volume 32, Number 6, November 2022
- Mohamed L. Seghier:
It is time to make neuroimaging research data beneficial to the participants. 1819-1821
- Martti Juhola, Henry Joutsijoki, Kirsi Penttinen, Disheet Shah, Katriina Aalto-Setälä:
A method to measure data complexity of a complicated medical data set. 1822-1831 - Thanh-Hai Nguyen, Huong Hoang Luong, Phat Tan Phan, Hung Nguyen Duc Huy, Duong Ly, Duc Minh Phan, Tin Trung Do:
HS-UNET-ID: An approach for human skin classification integrating between UNET and improved dense convolutional network. 1832-1845 - B. Chitra, S. S. Kumar:
Early cervical cancer diagnosis using Sooty tern-optimized CNN-LSTM classifier. 1846-1860 - Mamta Juneja, Sumindar Kaur Saini, Rajarshi Acharjee, Sambhav Kaul, Niharika Thakur, Prashant Jindal:
PC-SNet for automated detection of prostate cancer in multiparametric-magnetic resonance imaging. 1861-1879 - S. R. Sannasi Chakravarthy, Harikumar Rajaguru:
SKMAT-U-Net architecture for breast mass segmentation. 1880-1888 - Atefe Aghaei, Mohsen Ebrahimi Moghaddam, Hamed Malek:
Interpretable ensemble deep learning model for early detection of Alzheimer's disease using local interpretable model-agnostic explanations. 1889-1902 - Adam Hasse, Julian Bertini, Sean Foxley, Yong Jeong, Adil Javed, Timothy J. Carroll:
Application of a novel T1 retrospective quantification using internal references (T1-REQUIRE) algorithm to derive quantitative T1 relaxation maps of the brain. 1903-1915 - Sabeena Karim Kutty, Gopakumar Chandrasekhara Menon:
Enhancing convolutional neural network model with spectral features for the identification of cervical dysplasia. 1916-1927 - Qing Yang, Qingyuan Yan, Wuxia Zhang, Mayang Hao, Hao Chen:
Deep feature enhancement and Xgboost network for multi-organ classification. 1928-1940 - Vernon Furtado da Silva, Diego Augusto Santos Silva, Priscila Custódio Martins, Mauricio Rocha Calomeni, Ivete de Aquino Freire, Angeliete Garcês Militão, Célio José Borges, Guanis de Barros Vilela Junior, Mario Antônio de Moraes, Antônio José Rocha Martins Silva, Daniel de Almeida Marinho, Domingos Edno Castro Ribeiro, Edinilson Castro Ribeiro, João Rafael Valentim-Silva:
Effect of physical exercise and noninvasive brain stimulation on cognition and dementia of elderly people with frailty: A randomized study. 1941-1952 - Doaa Mahmoud-Ghoneim:
The effect of quantization at different resolutions on the classification of lesion texture in dermoscopic images using support vector machine. 1953-1962 - Mukta Sharma, Ayush Mandloi, Mahua Bhattacharya:
A novel DeepML framework for multi-classification of breast cancer based on transfer learning. 1963-1977 - Harun Bingol:
NCA-based hybrid convolutional neural network model for classification of cervical cancer on gauss-enhanced pap-smear images. 1978-1989 - Faruk Oztekin, Oguzhan Katar, Ferhat Sadak, Murat Aydogan, Tuba Talo Yildirim, Pawel Plawiak, Özal Yildirim, Muhammed Talo, Murat Karabatak:
Automatic semantic segmentation for dental restorations in panoramic radiography images using U-Net model. 1990-2001 - Libing Hu, Yongchun Zhang, Kaidi Chen, Saleh Mobayen:
A computer-aided melanoma detection using deep learning and an improved African vulture optimization algorithm. 2002-2016 - Remya Remani Sathyan, Gopakumar Chandrasekhara Menon, Hari Prasad, Hariharan Sreedharan, D. Jude Hemanth:
Deep learning-based semantic segmentation of interphase cells and debris from metaphase images. 2017-2033 - Poonguzhali Elangovan, Malaya Kumar Nath:
En-ConvNet: A novel approach for glaucoma detection from color fundus images using ensemble of deep convolutional neural networks. 2034-2048 - Kubilay Muhammed Sünnetci, Ahmet Alkan:
Lung cancer detection by using probabilistic majority voting and optimization techniques. 2049-2065 - Guanzhong Zhang, Shengsheng Wang:
Dense and shuffle attention U-Net for automatic skin lesion segmentation. 2066-2079 - Jiffy Joseph, Challa Hemanth, Pournami Pulinthanathu Narayanan, Jayaraj Pottekkattuvalappil Balakrishnan, Niyas Puzhakkal:
Computed tomography image generation from magnetic resonance imaging using Wasserstein metric for MR-only radiation therapy. 2080-2093 - Kanimozhi Ganesan, Pichai Shanmugavadivu, Muthu Subash Kavitha, Masayoshi Takahashi:
Data imputation in deep neural network to enhance breast cancer detection. 2094-2106 - Panduranga Vital Terlapu, Stalin Babu Gedela, Vijay Kumar Gangu, Rambabu Pemula:
Intelligent diagnosis system of hepatitis C virus: A probabilistic neural network based approach. 2107-2136 - Marriam Nawaz, Tahira Nazir, Momina Masood, Farooq Ali, Muhammad Attique Khan, Usman Tariq, Naveera Sahar, Robertas Damasevicius:
Melanoma segmentation: A framework of improved DenseNet77 and UNET convolutional neural network. 2137-2153 - Ansi Pan, Shengzhou Xu:
Mammographic mass recognition using feature reuse and channel attention mechanism. 2154-2162 - Sakambhari Mahapatra, Sanjay Agrawal:
An optimal statistical feature-based transformation function for enhancement of retinal images using adaptive enhanced leader particle swarm optimization. 2163-2183 - Guangzhe Zhao, Shuai Shao, Min Yu:
Key techniques for classification of thorax diseases based on deep learning. 2184-2197 - Phu-Hung Dinh, Long Giang Nguyen:
A new medical image enhancement algorithm using adaptive parameters. 2198-2218 - Karthikamani R, Harikumar Rajaguru:
Detection of liver abnormalities - A new paradigm in medical image processing and classification techniques. 2219-2239 - Sushitha Susan Joseph, Aju Dennisan:
An affinity propagated clustering aided computerized Inherent Seeded Region Growing and Deep learned Marching Cubes Algorithm (ISRG-DMCA) based three dimensional image reconstruction approach. 2240-2254 - Volkan Akdogan, Vedat Özkaner, Fatih Özkan Alkurt, Muharrem Karaaslan:
Theoretical and experimental sensing of bone healing by microwave approach. 2255-2261 - Dhiren Pandit, Jayesh M. Dhodiya, Yogeshwari F. Patel:
Molecular cancer classification on microarrays gene expression data using wavelet-based deep convolutional neural network. 2262-2280 - Guangdong Liu, Kaiyin Zhang:
A modified contrast source inversion method for microwave tomographic imaging of Debye dispersive media. 2281-2291
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