A review on automated cancer detection in medical images using machine learning and deep learning based computational techniques: Challenges and …
Cancer is one of the most deadly diseases diagnosed among the population across the
globe so far. The number of cases is increasing at a high pace each year that subsequently …
globe so far. The number of cases is increasing at a high pace each year that subsequently …
Cervical cancer: Automation of pap test screening
MT Rezende, AGC Bianchi… - Diagnostic …, 2021 - Wiley Online Library
Background Cervical cancer progresses slowly, increasing the chance of early detection of
pre‐neoplastic lesions via Pap exam test and subsequently preventing deaths. However, the …
pre‐neoplastic lesions via Pap exam test and subsequently preventing deaths. However, the …
An optimized deep learning model using Mutation-based Atom Search Optimization algorithm for cervical cancer detection
B Chitra, SS Kumar - Soft Computing, 2021 - Springer
The cervical cancer patient's death rate can be minimized by accurate and early detection of
cervical cancer (CC). One of the popular techniques called the Pap test or Pap smear is …
cervical cancer (CC). One of the popular techniques called the Pap test or Pap smear is …
Nucleus segmentation of cervical cytology images based on multi-scale fuzzy clustering algorithm
J Huang, T Wang, D Zheng, Y He - Bioengineered, 2020 - Taylor & Francis
In the screening of cervical cancer cells, accurate identification and segmentation of nucleus
in cell images is a key part in the early diagnosis of cervical cancer. Overlapping, uneven …
in cell images is a key part in the early diagnosis of cervical cancer. Overlapping, uneven …
A new cervical cytology dataset for nucleus detection and image classification (Cervix93) and methods for cervical nucleus detection
HA Phoulady, PR Mouton - arXiv preprint arXiv:1811.09651, 2018 - arxiv.org
Analyzing Pap cytology slides is an important tasks in detecting and grading precancerous
and cancerous cervical cancer stages. Processing cytology images usually involve …
and cancerous cervical cancer stages. Processing cytology images usually involve …
What is the state of the art of computer vision-assisted cytology? A Systematic Literature Review
AV Matias, JGA Amorim, LAB Macarini… - … Medical Imaging and …, 2021 - Elsevier
Cytology is a low-cost and non-invasive diagnostic procedure employed to support the
diagnosis of a broad range of pathologies. Cells are harvested from tissues by aspiration or …
diagnosis of a broad range of pathologies. Cells are harvested from tissues by aspiration or …
Nucleus segmentation of cervical cytology images based on depth information
T Wang, J Huang, D Zheng, Y He - IEEE Access, 2020 - ieeexplore.ieee.org
In cervical cancer screening, accurate segmentation of cervical nucleus is a key part in the
early diagnosis of cervical cancer. However, the cervical nucleus segmentation faces many …
early diagnosis of cervical cancer. However, the cervical nucleus segmentation faces many …
An improved ensemble deep belief model (EDBM) for pap-smear cell image classification
M Benhari, R Hossseini - Multimedia Tools and Applications, 2024 - Springer
Applications of deep learning models for medical image analysis have been concentrated in
recent years. This study presents an improved automatic Deep Learning Ensemble model to …
recent years. This study presents an improved automatic Deep Learning Ensemble model to …
[HTML][HTML] A contour property based approach to segment nuclei in cervical cytology images
Background Segmentation of nuclei in cervical cytology pap smear images is a crucial stage
in automated cervical cancer screening. The task itself is challenging due to the presence of …
in automated cervical cancer screening. The task itself is challenging due to the presence of …
Segmentation of overlapping cells in cervical cytology images: a survey
Pap smear testing is crucial for early diagnosis of cervical cancer, but cell overlapping poses
a significant challenge to diagnostic accuracy, as improper processing of overlapping cells …
a significant challenge to diagnostic accuracy, as improper processing of overlapping cells …