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
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
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
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
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
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
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...

Impact of the Genius Digital Diagnostics System on workflow and accuracy compared with the ThinPrep Imaging System for review of ThinPrep Papanicolaou tests.

American journal of clinical pathology
OBJECTIVE: In this study, we compared the workflow of the Genius Digital Diagnostics System (Hologic, Inc) with our current workflow based on the ThinPrep Imaging System (Hologic, Inc) to assess potential efficiencies associated with digitalization o...

Discriminant study of cervical squamous cells based on computer image analysis.

Medicine
This study aimed to explore a discriminant method for cervical squamous epithelial cells based on computer image analysis to establish a foundation for artificial intelligence diagnosis of cervical cancer. A total of 1682 cells were captured from 53 ...

CervicalMethDx: A Precision DNA Methylation Test to Identify Risk of High-Grade Intraepithelial Lesions in Cervical Cancer Screening Algorithms.

Cancer prevention research (Philadelphia, Pa.)
UNLABELLED: Cervical cancer is one of the most common cancers in women. Despite progress in prevention and success in early detection through cytologic screening and human papillomavirus (HPV) detection, there remains a challenge in triaging women ap...