Accurate deep learning model using semi-supervised learning and Noisy Student for cervical cancer screening in low magnification images

Y Kurita, S Meguro, N Tsuyama, I Kosugi, Y Enomoto… - Plos one, 2023 - journals.plos.org
Deep learning technology has been used in the medical field to produce devices for clinical
practice. Deep learning methods in cytology offer the potential to enhance cancer screening …

DGLT-Fusion: A decoupled global–local infrared and visible image fusion transformer

X Yang, H Huo, R Wang, C Li, X Liu, J Li - Infrared Physics & Technology, 2023 - Elsevier
Abstract Convolution Neural Networks (CNN) and generative adversarial networks (GAN)
based approaches have achieved substantial performance in image fusion field. However …

Segmentation of overlapping cells in cervical cytology images: a survey

E Chen, HN Ting, JH Chuah, J Zhao - IEEE Access, 2024 - ieeexplore.ieee.org
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 …

Deep learning framework for mobile microscopy

A Kornilova, M Salnikov, O Novitskaya… - 2021 IEEE 18th …, 2021 - ieeexplore.ieee.org
Mobile microscopy is a promising technology to assist and to accelerate disease
diagnostics, with its widespread adoption being hindered by the mediocre quality of …

Smart mobile microscopy: towards fully-automated digitization

A Kornilova, I Kirilenko, D Iarosh, V Kutuev… - Proceedings of the …, 2022 - Springer
Mobile microscopy is a newly formed field that emerged from a combination of optical
microscopy capabilities and spread, functionality, and ever-increasing computing resources …

[PDF][PDF] MMDF: Mobile Microscopy Deep Framework

A Kornilova, M Salnikov, O Novitskaya, M Begicheva… - CoRR, 2020 - researchgate.net
In the last decade, a huge step was done in the field of mobile microscopes development as
well as in the field of mobile microscopy application to real-life disease diagnostics and a lot …