Internet of health things-driven deep learning system for detection and classification of cervical cells using transfer learning
Cervical cancer is one of the fastest growing global health problems and leading cause of
mortality among women of developing countries. Automated Pap smear cell recognition and …
mortality among women of developing countries. Automated Pap smear cell recognition and …
The application of deep learning based diagnostic system to cervical squamous intraepithelial lesions recognition in colposcopy images
C Yuan, Y Yao, B Cheng, Y Cheng, Y Li, Y Li, X Liu… - Scientific reports, 2020 - nature.com
Background Deep learning has presented considerable potential and is gaining more
importance in computer assisted diagnosis. As the gold standard for pathologically …
importance in computer assisted diagnosis. As the gold standard for pathologically …
Classification of cervical cancer using Deep Learning Algorithm
A Tripathi, A Arora, A Bhan - 2021 5th International Conference …, 2021 - ieeexplore.ieee.org
Cervical cancer is one of the most prevalent diseases in women ranking fourth in worldwide,
mostly occurring in less-developed countries. This is perceived when certain vagaries occur …
mostly occurring in less-developed countries. This is perceived when certain vagaries occur …
Cervix type and cervical cancer classification system using deep learning techniques
LW Habtemariam, ET Zewde… - Medical devices: evidence …, 2022 - Taylor & Francis
Purpose Cervical cancer is the 4th most common cancer among women, worldwide.
Incidence and mortality rates are consistently increasing, especially in developing countries …
Incidence and mortality rates are consistently increasing, especially in developing countries …
DCAVN: Cervical cancer prediction and classification using deep convolutional and variational autoencoder network
Early detection, early diagnosis and classification of the cancer type facilitates faster disease
management of patients. Cervical cancer is fourth most pervasive cancer type which affects …
management of patients. Cervical cancer is fourth most pervasive cancer type which affects …
ColpoNet for automated cervical cancer screening using colposcopy images
Cervical cancer is one among the trivial forms of cancer that counts for 6.6% of all females
cancers with an estimated 570,000 new cases in 2018. The mortality rate due to cervical …
cancers with an estimated 570,000 new cases in 2018. The mortality rate due to cervical …
[PDF][PDF] Cervical cancer classification using combined machine learning and deep learning approach
Cervical cancer is screened by pap smear methodology for detection and classification
purposes. Pap smear images of the cervical region are employed to detect and classify the …
purposes. Pap smear images of the cervical region are employed to detect and classify the …
VisionCervix: Papanicolaou cervical smears classification using novel CNN-Vision ensemble approach
About half a million women in the world are affected by cervical cancer and about 0.3 million
deaths occur per year due to cervical cancer. Cytologists perform Pap-smear tests to screen …
deaths occur per year due to cervical cancer. Cytologists perform Pap-smear tests to screen …
Diagnosis of cervical cancer based on ensemble deep learning network using colposcopy images
V Chandran, MG Sumithra, A Karthick… - BioMed Research …, 2021 - Wiley Online Library
Traditional screening of cervical cancer type classification majorly depends on the
pathologist's experience, which also has less accuracy. Colposcopy is a critical component …
pathologist's experience, which also has less accuracy. Colposcopy is a critical component …
Adaptive pruning of transfer learned deep convolutional neural network for classification of cervical pap smear images
P Wang, J Wang, Y Li, L Li, H Zhang - IEEE Access, 2020 - ieeexplore.ieee.org
Automatic classification of cervical Pap smear images plays a key role in computer-aided
cervical cancer diagnosis. Conventional classification approaches rely on cell segmentation …
cervical cancer diagnosis. Conventional classification approaches rely on cell segmentation …