Cervical Lesion Classification Method Based on Cross-Validation Decision Fusion Method of Vision Transformer and DenseNet
出版年份 2022 全文链接
标题
Cervical Lesion Classification Method Based on Cross-Validation Decision Fusion Method of Vision Transformer and DenseNet
作者
关键词
-
出版物
Journal of Healthcare Engineering
Volume 2022, Issue -, Pages 1-10
出版商
Hindawi Limited
发表日期
2022-05-15
DOI
10.1155/2022/3241422
参考文献
相关参考文献
注意:仅列出部分参考文献,下载原文获取全部文献信息。- A Fast Hybrid Classification Algorithm with Feature Reduction for Medical Images
- (2022) Hanan Ahmed Hosni Mahmoud et al. Applied Bionics and Biomechanics
- MDC-net: A new convolutional neural network for nucleus segmentation in histopathology images with distance maps and contour information
- (2021) Xiaoming Liu et al. COMPUTERS IN BIOLOGY AND MEDICINE
- Weakly Supervised Segmentation of COVID19 Infection with Scribble Annotation on CT Images
- (2021) Xiaoming Liu et al. PATTERN RECOGNITION
- A fuzzy rank-based ensemble of CNN models for classification of cervical cytology
- (2021) Ankur Manna et al. Scientific Reports
- Integration of Global and Local Features for Specular Reflection Inpainting in Colposcopic Images
- (2021) Xiaoxia Wang et al. Journal of Healthcare Engineering
- Computer-aided diagnostic system based on deep learning for classifying colposcopy images
- (2021) Lu Liu et al. Annals of Translational Medicine
- Cancer statistics, 2020
- (2020) Rebecca L. Siegel et al. CA-A CANCER JOURNAL FOR CLINICIANS
- ColpoNet for automated cervical cancer screening using colposcopy images
- (2020) Sumindar Kaur Saini et al. MACHINE VISION AND APPLICATIONS
- The application of deep learning based diagnostic system to cervical squamous intraepithelial lesions recognition in colposcopy images
- (2020) Chunnv Yuan et al. Scientific Reports
- Classification of cervical neoplasms on colposcopic photography using deep learning
- (2020) Bum-Joo Cho et al. Scientific Reports
- Multimodal MR Image Synthesis Using Gradient Prior and Adversarial Learning
- (2020) Xiaoming Liu et al. IEEE Journal of Selected Topics in Signal Processing
- Development and validation of an artificial intelligence system for grading colposcopic impressions and guiding biopsies
- (2020) Peng Xue et al. BMC Medicine
- Cervical precancerous lesions classification using pre-trained densely connected convolutional networks with colposcopy images
- (2019) Tao Zhang et al. Biomedical Signal Processing and Control
- Detection of cervical lesion region from colposcopic images based on feature reselection
- (2019) Bing Bai et al. Biomedical Signal Processing and Control
- Deep learning for image-based cancer detection and diagnosis − A survey
- (2018) Zilong Hu et al. PATTERN RECOGNITION
- Cervical image classification based on image segmentation preprocessing and a CapsNet network model
- (2018) XiaoQing Zhang et al. INTERNATIONAL JOURNAL OF IMAGING SYSTEMS AND TECHNOLOGY
- An Observational Study of Deep Learning and Automated Evaluation of Cervical Images for Cancer Screening
- (2018) Liming Hu et al. JNCI-Journal of the National Cancer Institute
- Development of Algorithms for Automated Detection of Cervical Pre-Cancers With a Low-Cost, Point-of-Care, Pocket Colposcope
- (2018) Mercy Nyamewaa Asiedu et al. IEEE TRANSACTIONS ON BIOMEDICAL ENGINEERING
- A survey on deep learning in medical image analysis
- (2017) Geert Litjens et al. MEDICAL IMAGE ANALYSIS
- Multi-feature based benchmark for cervical dysplasia classification evaluation
- (2017) Tao Xu et al. PATTERN RECOGNITION
- Multimodal Entity Coreference for Cervical Dysplasia Diagnosis
- (2015) Dezhao Song et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- Domain-Specific Image Analysis for Cervical Neoplasia Detection Based on Conditional Random Fields
- (2011) S Y Park et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- Effectiveness of VIA, Pap, and HPV DNA Testing in a Cervical Cancer Screening Program in a Peri-Urban Community in Andhra Pradesh, India
- (2010) Patti E. Gravitt et al. PLoS One
Discover Peeref hubs
Discuss science. Find collaborators. Network.
Join a conversationPublish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn More