Computer-Aided Gastrointestinal Diseases Analysis From Wireless Capsule Endoscopy: A Framework of Best Features Selection
暂无分享,去创建一个
Seifedine Kadry | Venkatesan Rajinikanth | Muhammad Attique Khan | Majed Alhaisoni | Yunyoung Nam | Yudong Zhang | Muhammad Shahzad Sarfraz | M. Alhaisoni | S. Kadry | V. Rajinikanth | M. A. Khan | Yunyoung Nam | Yudong Zhang | M. Sarfraz | Majed Alhaisoni
[1] Yixuan Yuan,et al. Deep learning for polyp recognition in wireless capsule endoscopy images , 2017, Medical physics.
[2] Tanzila Saba,et al. Region Extraction and Classification of Skin Cancer: A Heterogeneous framework of Deep CNN Features Fusion and Reduction , 2019, Journal of Medical Systems.
[3] Geoffrey E. Hinton,et al. ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.
[4] Michael Riegler,et al. Detection and Classification of Bleeding Region in WCE Images using Color Feature , 2017, CBMI.
[5] C. Shahnaz,et al. An automatic ulcer detection scheme using histogram in YIQ domain from wireless capsule endoscopy images , 2017, TENCON 2017 - 2017 IEEE Region 10 Conference.
[6] Klaus Mergener. Update on the use of capsule endoscopy. , 2008, Gastroenterology & hepatology.
[7] Mohamed El Ansari,et al. Computer-aided diagnosis system for colon abnormalities detection in wireless capsule endoscopy images , 2017, Multimedia Tools and Applications.
[8] Jamal Hussain Shah,et al. AUTOMATED ULCER AND BLEEDING CLASSIFICATION FROM WCE IMAGES USING MULTIPLE FEATURES FUSION AND SELECTION , 2018, Journal of Mechanics in Medicine and Biology.
[9] Andrew Zisserman,et al. Very Deep Convolutional Networks for Large-Scale Image Recognition , 2014, ICLR.
[10] Milan Tuba,et al. An algorithm for automated segmentation for bleeding detection in endoscopic images , 2017, 2017 International Joint Conference on Neural Networks (IJCNN).
[11] K. Kim,et al. Spotting malignancies from gastric endoscopic images using deep learning , 2019, Surgical Endoscopy.
[12] Max Q.-H. Meng,et al. Tumor Recognition in Wireless Capsule Endoscopy Images Using Textural Features and SVM-Based Feature Selection , 2012, IEEE Transactions on Information Technology in Biomedicine.
[13] Muhammad Sharif,et al. Stomach Deformities Recognition Using Rank-Based Deep Features Selection , 2019, Journal of Medical Systems.
[14] Muhammad Rashid,et al. Classification of gastrointestinal diseases of stomach from WCE using improved saliency-based method and discriminant features selection , 2019, Multimedia Tools and Applications.
[15] Shi-Min Hu,et al. Global contrast based salient region detection , 2011, CVPR 2011.
[16] Robby T. Tan,et al. Visibility in bad weather from a single image , 2008, 2008 IEEE Conference on Computer Vision and Pattern Recognition.
[17] João Paulo Papa,et al. Barrett's Esophagus Identification Using Optimum-Path Forest , 2017, 2017 30th SIBGRAPI Conference on Graphics, Patterns and Images (SIBGRAPI).
[18] Sajjad Waheed,et al. An Automatic Gastrointestinal Polyp Detection System in Video Endoscopy Using Fusion of Color Wavelet and Convolutional Neural Network Features , 2017, Int. J. Biomed. Imaging.
[19] Lin Zhu,et al. Hyperspectral Images Classification With Gabor Filtering and Convolutional Neural Network , 2017, IEEE Geoscience and Remote Sensing Letters.
[20] Bogdan Kwolek,et al. Face Detection Using Convolutional Neural Networks and Gabor Filters , 2005, ICANN.
[21] Jamal Hussain Shah,et al. Lungs cancer classification from CT images: An integrated design of contrast based classical features fusion and selection , 2020, Pattern Recognit. Lett..
[22] Chunguo Wu,et al. Particle swarm optimization based on dimensional learning strategy , 2019, Swarm Evol. Comput..
[23] Khan A. Wahid,et al. Performance assessment of a bleeding detection algorithm for endoscopic video based on classifier fusion method and exhaustive feature selection , 2018, Biomed. Signal Process. Control..
[24] Chen Chen,et al. Gabor Convolutional Networks , 2017, 2018 IEEE Winter Conference on Applications of Computer Vision (WACV).
[25] Muhammad Rashid,et al. Deep CNN and geometric features-based gastrointestinal tract diseases detection and classification from wireless capsule endoscopy images , 2019, J. Exp. Theor. Artif. Intell..
[26] Michael Riegler,et al. KVASIR: A Multi-Class Image Dataset for Computer Aided Gastrointestinal Disease Detection , 2017, MMSys.
[27] Lihua Li,et al. Computer-aided detection of small intestinal ulcer and erosion in wireless capsule endoscopy images , 2018, Physics in medicine and biology.
[28] Mohamed El Ansari,et al. Computer-aided diagnosis system for ulcer detection in wireless capsule endoscopy videos , 2017, 2017 International Conference on Advanced Technologies for Signal and Image Processing (ATSIP).
[29] Muhammad Rashid,et al. An integrated framework of skin lesion detection and recognition through saliency method and optimal deep neural network features selection , 2019, Neural Computing and Applications.
[30] Muhammad Younus Javed,et al. An implementation of optimized framework for action classification using multilayers neural network on selected fused features , 2019, Pattern Analysis and Applications.
[31] Klaus Schöffmann,et al. Content-based processing and analysis of endoscopic images and videos: A survey , 2017, Multimedia Tools and Applications.
[32] Lianru Gao,et al. Deep CNN With Multi-Scale Rotation Invariance Features for Ship Classification , 2018, IEEE Access.
[33] Hu Yao,et al. Gabor Feature Based Convolutional Neural Network for Object Recognition in Natural Scene , 2016, 2016 3rd International Conference on Information Science and Control Engineering (ICISCE).
[34] Omid Haji Maghsoudi,et al. A computer aided method to detect bleeding, tumor, and disease regions in Wireless Capsule Endoscopy , 2016, 2016 IEEE Signal Processing in Medicine and Biology Symposium (SPMB).
[35] Max Q.-H. Meng,et al. Saliency Based Ulcer Detection for Wireless Capsule Endoscopy Diagnosis , 2015, IEEE Transactions on Medical Imaging.
[36] Mohinder Malhotra. Single Image Haze Removal Using Dark Channel Prior , 2016 .
[37] Amjad Rehman,et al. Hand-crafted and deep convolutional neural network features fusion and selection strategy: An application to intelligent human action recognition , 2020, Appl. Soft Comput..
[38] Jian Ping Li,et al. Active deep neural network features selection for segmentation and recognition of brain tumors using MRI images , 2020, Pattern Recognit. Lett..
[39] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[40] Muhammad Sharif,et al. Brain tumor detection and classification: A framework of marker‐based watershed algorithm and multilevel priority features selection , 2019, Microscopy research and technique.
[41] Carlos S. Lima,et al. Automatic detection of small bowel tumors in capsule endoscopy based on color curvelet covariance statistical texture descriptors , 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.
[42] Muhammad Awais,et al. Lungs nodule detection framework from computed tomography images using support vector machine , 2019, Microscopy research and technique.
[43] Muhammad Younus Javed,et al. Multi-level features fusion and selection for human gait recognition: an optimized framework of Bayesian model and binomial distribution , 2019, Int. J. Mach. Learn. Cybern..
[44] Zahid Iqbal,et al. Detection and classification of citrus diseases in agriculture based on optimized weighted segmentation and feature selection , 2018, Comput. Electron. Agric..
[45] Noha Ghatwary,et al. Esophageal Abnormality Detection Using DenseNet Based Faster R-CNN With Gabor Features , 2019, IEEE Access.
[46] Aamir Saeed Malik,et al. Feature Selection and Classification of Ulcerated Lesions Using Statistical Analysis for WCE Images , 2017 .
[47] Abbas Jamalipour,et al. Machine Learning Inspired Sound-Based Amateur Drone Detection for Public Safety Applications , 2019, IEEE Transactions on Vehicular Technology.
[48] H. Duan,et al. Gastric precancerous diseases classification using CNN with a concise model , 2017, PloS one.
[49] Saurabh Sahu,et al. SCL-UMD at the Medico Task-MediaEval 2017: Transfer Learning based Classification of Medical Images , 2017, MediaEval.
[50] Mudassar Raza,et al. Object detection and classification: a joint selection and fusion strategy of deep convolutional neural network and SIFT point features , 2018, Multimedia Tools and Applications.
[51] Nader Karimi,et al. Segmentation of Bleeding Regions in Wireless Capsule Endoscopy Images an Approach for inside Capsule Video Summarization , 2018, ArXiv.
[52] Muhammad Sharif,et al. Developed Newton-Raphson based deep features selection framework for skin lesion recognition , 2020, Pattern Recognit. Lett..
[53] Max Q.-H. Meng,et al. Bleeding Frame and Region Detection in the Wireless Capsule Endoscopy Video , 2016, IEEE Journal of Biomedical and Health Informatics.