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ORCIDInternational Journal of Imaging Systems and Technology, Volume 33
Volume 33, Number 1, January 2023
EDITORIAL
- Mohamed L. Seghier:
Preparing a successful Special Issue proposal. 3-5
RESEARCH ARTICLES
- Lu Ma
, Shuni Song, Liting Guo, Wenjun Tan, Lisheng Xu:
COVID-19 lung infection segmentation from chest CT images based on CAPA-ResUNet. 6-17 - Harshal A. Sanghvi, Riki H. Patel, Ankur Agarwal, Shailesh Gupta, Vivek Sawhney, Abhijit S. Pandya:
A deep learning approach for classification of COVID and pneumonia using DenseNet-201. 18-38 - Harsh Gupta, Naman Bansal, Swati Garg, Hritesh Mallik, Anju Prabha, Jyoti Yadav:
A hybrid convolutional neural network model to detect COVID-19 and pneumonia using chest X-ray images. 39-52 - Pu Yan, Gang Wang, Jie Chen, Qingwei Tang, Heng Xu:
Skin lesion classification based on the VGG-16 fusion residual structure. 53-68 - Oznur Ozaltin, Orhan Coskun, Ozgur Yeniay, Abdulhamit Subasi:
Classification of brain hemorrhage computed tomography images using OzNet hybrid algorithm. 69-91 - Sumod Sundar, Sumathy Subramanian:
An effective deep learning model for grading abnormalities in retinal fundus images using variational auto-encoders. 92-107 - Uma Yadav, Ashish K. Sharma:
A novel automated depression detection technique using text transcript. 108-122 - Debayan Bhattacharya, Dennis Eggert, Christian Betz, Alexander Schlaefer:
Squeeze and multi-context attention for polyp segmentation. 123-142 - Tongyuan Huang, Yao Liu:
Research on the magnetic resonance imaging brain tumor segmentation algorithm based on DO-UNet. 143-157 - Yibeltal Tamyalew, Ayodeji Olalekan Salau, Aleka Melese Ayalew:
Detection and classification of large bowel obstruction from X-ray images using machine learning algorithms. 158-174 - Seenia Francis, Goutham Pooloth, Sai Bala Subrahmanyam Singam, Niyas Puzhakkal, Pournami Pulinthanathu Narayanan, Jayaraj Pottekkattuvalappil Balakrishnan:
SABOS-Net: Self-supervised attention based network for automatic organ segmentation of head and neck CT images. 175-191 - Bohan Yin, Shengsheng Wang, Shuzhen Lu, Guangyao Wang, Liyan Dong:
Error analysis driven network modification for surgical tools detection in laparoscopic frames. 192-203 - Mili Rosline Mathews, Sharafudeen Thaha Mohammed Anzar:
A lightweight deep learning model for retinal optical coherence tomography image classification. 204-216 - Tiejun Yang, Xinhao Bai, Xiaojuan Cui, Yuehong Gong, Lei Li:
DAU-Net: An unsupervised 3D brain MRI registration model with dual-attention mechanism. 217-229 - M. Jeya Sundari, N. C. Brintha:
Factorization-based active contour segmentation and pelican optimization-based modified bidirectional long short-term memory for ovarian tumor detection. 230-245 - Rajneesh Kumar Patel, Manish Kashyap:
Automated screening of glaucoma stages from retinal fundus images using BPS and LBP based GLCM features. 246-261 - Madan Parajuli, Mohamed Shaban, Thuy L. Phung:
Automated differentiation of skin melanocytes from keratinocytes in high-resolution histopathology images using a weakly-supervised deep-learning framework. 262-275 - Salwan Tajjour, Sonia Garg, Shyam Singh Chandel, Diksha Sharma:
A novel hybrid artificial neural network technique for the early skin cancer diagnosis using color space conversions of original images. 276-286 - Bakul Gohel, Mahish Khare:
EEG/MEG source imaging in the absence of subject's brain MRI scan: Perspective on co-registration and MRI selection approach. 287-298 - Jun Wu, Yaxin Zhang, Zhitao Xiao, Fang Zhang, Lei Geng:
Automated segmentation of diabetic macular edema in OCT B-scan images based on RCU-Net. 299-311 - Wei Guo, Shijie Liu, Zhaoxuan Gong, Guodong Zhang, Xiran Jiang:
Cascaded networks for the embryo classification on microscopic images using the residual external-attention. 312-322 - Asieh Khosravanian, Mohammad Rahmanimanesh, Parviz Keshavarzi, Saeed Mozaffari:
Enhancing level set brain tumor segmentation using fuzzy shape prior information and deep learning. 323-339 - Gurinderjeet Kaur, Prashant Singh Rana, Vinay Arora:
Deep learning and machine learning-based early survival predictions of glioblastoma patients using pre-operative three-dimensional brain magnetic resonance imaging modalities. 340-361 - Shan Jin, Hongming Xu, Yue Dong, Xinyu Hao, Fengying Qin, Qi Xu, Yong Zhu, Fengyu Cong:
Automatic cervical cancer segmentation in multimodal magnetic resonance imaging using an EfficientNet encoder in UNet++ architecture. 362-377 - Sinan Altun, Ahmet Alkan:
LSS-net: 3-dimensional segmentation of the spinal canal for the diagnosis of lumbar spinal stenosis. 378-388 - Xiaoyan Fan, Zhanquan Sun, Engang Tian, Zhong Yin, Gaoyu Cao:
Medical image contrast enhancement based on improved sparrow search algorithm. 389-402 - Haotian Zhang, Ning Jia, Keqiang Zhuo, Weidong Zhao:
Retinal fundus image registration framework using Bayesian integration and asymmetric Gaussian mixture model. 403-418 - Diana Baby, Sujitha Juliet, M. M. Anishin Raj:
An efficient lymphocytic leukemia detection based on EfficientNets and ensemble voting classifier. 419-426 - N. Nithya, M. S. K. Manikandan:
Resolution improvement using enriched Krylov subspace for microwave tomography breast imaging system. 427-442
Volume 33, Number 2, March 2023
RESEARCH ARTICLES
- Ali Abbasian Ardakani, Afshin Mohammadi, Fariborz Faeghi, U. Rajendra Acharya:
Performance evaluation of 67 denoising filters in ultrasound images: A systematic comparison analysis. 445-464 - Syed Sajid Hussain, Jainy Sachdeva, Chirag Kamal Ahuja, Abhiav Singh:
Enc-Unet: A novel method for Glioma segmentation. 465-482 - Anjan Gudigar, U. Raghavendra, Tejaswi N. Rao, Jyothi Samanth, Venkatesan Rajinikanth, Suresh Chandra Satapathy, Edward J. Ciaccio, Wai-Yee Chan, U. Rajendra Acharya:
FFCAEs: An efficient feature fusion framework using cascaded autoencoders for the identification of gliomas. 483-494 - Pallabi Sharma, Dipankar Das, Anmol Gautam, Bunil Kumar Balabantaray:
LPNet: A lightweight CNN with discrete wavelet pooling strategies for colon polyps classification. 495-510 - Angamuthu Rajasekaran Kavitha, Karthikeyan Palaniappan:
Brain tumor segmentation using a deep Shuffled-YOLO network. 511-522 - Jing Wang, Wenjuan Zhang, Rui Zhu:
A multimodal molecular image fusion method based on relative total variation and co-saliency detection. 523-546 - Heewon Yoon, Yongwon Cho, Kyung-Sik Ahn, Hee-Gone Lee, Chang Ho Kang, Beom Jin Park:
Using a convolutional neural network model to derive imaging landmarks for lumbar spine numbering on axial magnetic resonance images. 547-555 - Ellák Somfai, Benjámin Baffy, Kristian Fenech, Rita Hosszú, Dorina Korózs, Marcell Pólik, Miklós Sárdy, András Lorincz:
Handling dataset dependence with model ensembles for skin lesion classification from dermoscopic and clinical images. 556-571 - Muhammad Attique Khan, Awais Khan, Majed Alhaisoni, Abdullah Alqahtani, Shtwai Alsubai, Meshal Alharbi, Nazir Ahmed Malik, Robertas Damasevicius:
Multimodal brain tumor detection and classification using deep saliency map and improved dragonfly optimization algorithm. 572-587 - Nitika Goenka, Shamik Tiwari:
Alzheimer's detection using various feature extraction approaches using a multimodal multi-class deep learning model. 588-609 - Latifa Houria, Noureddine Belkhamsa, Assia Cherfa, Yazid Cherfa:
Multimodal magnetic resonance imaging for Alzheimer's disease diagnosis using hybrid features extraction and ensemble support vector machines. 610-621 - Zhiwei Ye, Zilun Song, Pengfei Li, Mingwei Wang, Wenguang Hou:
A modified threshold score-based multilevel thresholding segmentation technique for brain magnetic resonance images using opposition-based learning hybrid rice optimization algorithm. 622-643 - K. H. Vijaya Kumari, Soubhagya Sankar Barpanda:
Residual UNet with Dual Attention - An ensemble residual UNet with dual attention for multi-modal and multi-class brain MRI segmentation. 644-658 - Shobha Jose, Thomas George Selvaraj, Kenneth Samuel, Jobin T. Philip, Sairamya Nanjappan Jothiraj, Subathra Muthu Swamy Pandian, Vikram Shenoy Handiru, Suviseshamuthu Easter Selvan:
Intramuscular EMG classifier for detecting myopathy and neuropathy. 659-669 - Ming Meng, Zhichao Dong, Yunyuan Gao, Qingshan She:
Optimal channel and frequency band-based feature selection for motor imagery electroencephalogram classification. 670-679 - Ramzi Mahmoudi:
Ventricular segmentation and modeling using topological watershed transformation and harmonic state model. 680-700 - Geetha Sushama, Gopakumar Chandrasekhara Menon:
Attention augmented residual autoencoder for efficient polyp segmentation. 701-713 - Rupesh Mahamune, Shahedul Haque Laskar:
An automatic channel selection method based on the standard deviation of wavelet coefficients for motor imagery based brain-computer interfacing. 714-728 - P. Vaidehi Nayantara, Surekha Kamath, Manjunath Kanabagatte Nanjundappa, Rajagopal Kadavigere:
Automatic liver tumor segmentation on multiphase computed tomography volume using SegNet deep neural network and K-means clustering. 729-745 - Balakumaresan Ragupathy, Bharath Subramani, Selvapandian Arumugam:
A novel approach for MR brain tumor classification and detection using optimal CNN-SVM model. 746-759 - Muhammet Serdar Bugday, Mehmet Akcicek, Harun Bingol, Muhammed Yildirim:
Automatic diagnosis of ureteral stone and degree of hydronephrosis with proposed convolutional neural network, RelieF, and gradient-weighted class activation mapping based deep hybrid model. 760-769
CORRIGENDUM
- Correction to 'ORYX-MRSI: A fully-automated open-source software for proton magnetic resonance spectroscopic imaging data analysis'. 770
Volume 33, Number 3, May 2023
EDITORIAL
- Mohamed L. Seghier:
Using ChatGPT and other AI-assisted tools to improve manuscripts readability and language. 773-775
RESEARCH ARTICLES
- Mahmut Agrali, Volkan Kilic, Aytug Onan, Esra Meltem Koç, Ali Murat Koc, Rasit Eren Büyüktoka, Türker Acar, Zehra Adibelli:
DeepChestNet: Artificial intelligence approach for COVID-19 detection on computed tomography images. 776-788 - S. Jeevitha, K. Valarmathi:
A joint segmentation and classification framework for COVID-19 infection segmentation and detection from chest CT images. 789-806 - Rajneesh Kumar Patel, Manish Kashyap:
Automated diagnosis of COVID stages using texture-based Gabor features in variational mode decomposition from CT images. 807-821 - Sangeetha Balachandran, Vidhyapriya Ranganathan:
Semantic context-aware attention UNET for lung cancer segmentation and classification. 822-836 - Quan Sheng, Yutao Zhang, Haifeng Shi, Zhuqing Jiao:
Global iterative optimization framework for predicting cognitive function statuses of patients with end-stage renal disease. 837-852 - Muhammet Emin Sahin:
Image processing and machine learning-based bone fracture detection and classification using X-ray images. 853-865 - Dania Mushtaq, Tahir Mustafa Madni, Uzair Iqbal Janjua, Fozia Anwar, Ahmad Kakakhail:
An automatic gastric polyp detection technique using deep learning. 866-880 - Swati P. Pawar, Sanjay N. Talbar:
Multi-level deep learning based lung cancer classifier for classification based on tumour-node-metastasis approach. 881-894 - Necip Cinar, Mehmet Kaya, Buket Kaya:
A novel convolutional neural network-based approach for brain tumor classification using magnetic resonance images. 895-908 - Geetha Pavani Pappu, Sreekar Tankala, Krishna Talabhaktula, Birendra Biswal:
EANet: Multiscale autoencoder based edge attention network for fluid segmentation from SD-OCT images. 909-927 - Prasenjit Dhar, Suganya Devi Kothandapani, Satish Kumar Satti, Srinivasan Padmanabhan:
HPKNN: Hyper-parameter optimized KNN classifier for classification of poikilocytosis. 928-950 - Mehmet Ercan Nergiz:
Federated learning-based colorectal cancer classification by convolutional neural networks and general visual representation learning. 951-964 - Priyanka Arora, Parminder Singh, Akshay Girdhar, Rajesh Vijayvergiya:
Performance analysis of various denoising filters on intravascular ultrasound coronary artery images. 965-984 - Sandeep Singh Sengar, Christopher Meulengracht, Mikael Ploug Boesen, Anders Føhrby Overgaard, Henrik Gudbergsen, Janus Damm Nybing, Mathias Perslev, Erik Bjørnager Dam:
Multi-planar 3D knee MRI segmentation via UNet inspired architectures. 985-998 - Mustafa Gürman, Bülent Bilgehan, Özlem Sabuncu, Omid Mirzaei:
A powerful probabilistic model for noise analysis in medical images. 999-1013 - Mahesh Gour, Sweta Jain, Sushant Kaushal:
XCapsNet: A deep neural network for automated detection of diabetic retinopathy. 1014-1027 - Deepak Saini, Ashima Khosla, Trilok Chand, Devendra K. Chouhan, Mahesh Prakash:
Automated knee osteoarthritis severity classification using three-stage preprocessing method and VGG16 architecture. 1028-1047 - Ravindranath Kadirappa, Deivalakshmi Subbian, Pandeeswari Ramasamy, Seok-Bum Ko:
Histopathological carcinoma classification using parallel, cross-concatenated and grouped convolutions deep neural network. 1048-1061 - Yanyan Shi, Zhang Yuhang, Meng Wang, Gao Zhen, Dai Meng, Feng Fu:
Image reconstruction based on a modified bird swarm optimization algorithm for electrical impedance tomography. 1062-1072 - Prabhishek Singh, Manoj Diwakar:
Total variation-based ultrasound image despeckling using method noise thresholding in non-subsampled contourlet transform. 1073-1091 - Qi Ding, Navid Razmjooy:
An optimal diagnosis system for melanoma dermoscopy images based on enhanced design of horse herd optimizer. 1092-1107
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