AIMC Topic: Vaginal Smears
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Comparing Deep Learning Models for Multi-cell Classification in Liquid- based Cervical Cytology Image.
AMIA ... Annual Symposium proceedings. AMIA Symposium
Mar 4, 2020
Liquid-based cytology (LBC) is a reliable automated technique for the screening of Papanicolaou (Pap) smear data. It is an effective technique for collecting a majority of the cervical cells and aiding cytopathologists in locating abnormal cells. Mos...
Adaptation of CytoProcessor for cervical cancer screening of challenging slides.
Diagnostic cytopathology
May 20, 2019
BACKGROUND: Current automated cervical cytology screening systems require purchase of a dedicated preparation machine and use of a specific staining protocol. CytoProcessor (DATEXIM, Caen, France) is a new automated system, designed to integrate seam...
Artificial intelligence in cytopathology: a review of the literature and overview of commercial landscape.
Journal of the American Society of Cytopathology
Mar 25, 2019
Artificial intelligence (AI) has made impressive strides recently in interpreting complex images, thanks to improvements in deep learning techniques and increasing computational power. Researchers have started applying these advanced techniques to pa...
Deep learning-based super-resolution in coherent imaging systems.
Scientific reports
Mar 8, 2019
We present a deep learning framework based on a generative adversarial network (GAN) to perform super-resolution in coherent imaging systems. We demonstrate that this framework can enhance the resolution of both pixel size-limited and diffraction-lim...
DeepPap: Deep Convolutional Networks for Cervical Cell Classification.
IEEE journal of biomedical and health informatics
May 19, 2017
Automation-assisted cervical screening via Pap smear or liquid-based cytology (LBC) is a highly effective cell imaging based cancer detection tool, where cells are partitioned into "abnormal" and "normal" categories. However, the success of most trad...
Development of a cervical cancer progress prediction tool for human papillomavirus-positive Koreans: A support vector machine-based approach.
The Journal of international medical research
May 22, 2015
OBJECTIVES: To develop a Web-based tool to draw attention to patients positive for human papillomavirus (HPV) who have a high risk of progression to cervical cancer, in order to increase compliance with follow-up examinations and facilitate good doct...
Assessment of the efficacy and accuracy of cervical cytology screening with the Hologic Genius Digital Diagnostics System.
Cancer cytopathology
Jul 1, 2025
BACKGROUND: Medical technologies powered by artificial intelligence are quickly transforming into practical solutions by rapidly leveraging massive amounts of data processed via deep learning algorithms. There is a necessity to validate these innovat...
Implementing 100% quality control in a cervical cytology workflow using whole slide images and artificial intelligence provided by the Techcyte SureView™ System.
Cancer cytopathology
Jun 1, 2025
BACKGROUND: Recent advancements in digital pathology have extended into cytopathology. Laboratories screening cervical cytology specimens now choose between limited imaging options and traditional manual microscopy. The Techcyte SureView™ Cervical Cy...
Deep-Learning-Based Evaluation of Dual Stain Cytology for Cervical Cancer Screening: A New Paradigm.
Journal of the National Cancer Institute
Nov 2, 2021
Solving the problem of imbalanced dataset with synthetic image generation for cell classification using deep learning.
Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Nov 1, 2021
The low number of annotated training images and class imbalance in the field of machine learning is a common problem that is faced in many applications. With this paper, we focus on a clinical dataset where cells were extracted in a previous research...
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