AIMC Topic: Vaginal Smears
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CINNAMON-GUI: Revolutionizing Pap Smear Analysis with CNN-Based Digital Pathology Image Classification.
F1000Research
Aug 6, 2024
BACKGROUND: Medical imaging has seen significant advancements through machine learning, particularly convolutional neural networks (CNNs). These technologies have transformed the analysis of pathological images, enhancing the accuracy of diagnosing a...
Consistent and effective method to define the mouse estrous cycle stage by a deep learning-based model.
The Journal of endocrinology
May 6, 2024
The mouse estrous cycle is divided into four stages: proestrus (P), estrus (E), metestrus (M), and diestrus (D). The estrous cycle affects reproductive hormone levels in a wide variety of tissues. Therefore, to obtain reliable results from female mic...
Assessment of Efficacy and Accuracy of Cervical Cytology Screening With Artificial Intelligence Assistive System.
Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc
Apr 6, 2024
The role of artificial intelligence (AI) in pathology offers many exciting new possibilities for improving patient care. This study contributes to this development by identifying the viability of the AICyte assistive system for cervical screening, an...
Improving cervical cancer classification in PAP smear images with enhanced segmentation and deep progressive learning-based techniques.
Diagnostic cytopathology
Mar 22, 2024
OBJECTIVE: Cervical cancer, a prevalent and deadly disease among women, comes second only to breast cancer, with over 700 daily deaths. The Pap smear test is a widely utilized screening method for detecting cervical cancer in its early stages. Howeve...
Cervical cell's nucleus segmentation through an improved UNet architecture.
PloS one
Oct 3, 2023
Precise segmentation of the nucleus is vital for computer-aided diagnosis (CAD) in cervical cytology. Automated delineation of the cervical nucleus has notorious challenges due to clumped cells, color variation, noise, and fuzzy boundaries. Due to it...
Application of the sliding window method and Mask-RCNN method to nuclear recognition in oral cytology.
Diagnostic pathology
Aug 2, 2022
BACKGROUND: We aimed to develop an artificial intelligence (AI)-assisted oral cytology method, similar to cervical cytology. We focused on the detection of cell nuclei because the ratio of cell nuclei to cytoplasm increases with increasing cell malig...
Scrutinizing high-risk patients from ASC-US cytology via a deep learning model.
Cancer cytopathology
Mar 15, 2022
BACKGROUND: Atypical squamous cells of undetermined significance (ASC-US) is the most frequent but ambiguous abnormal Papanicolaou (Pap) interpretation and is generally triaged by high-risk human papillomavirus (hrHPV) testing before colposcopy. This...
Segmentation of Overlapping Cervical Cells with Mask Region Convolutional Neural Network.
Computational and mathematical methods in medicine
Oct 4, 2021
The task of segmenting cytoplasm in cytology images is one of the most challenging tasks in cervix cytological analysis due to the presence of fuzzy and highly overlapping cells. Deep learning-based diagnostic technology has proven to be effective in...
Artificial intelligence-assisted fast screening cervical high grade squamous intraepithelial lesion and squamous cell carcinoma diagnosis and treatment planning.
Scientific reports
Aug 10, 2021
Every year cervical cancer affects more than 300,000 people, and on average one woman is diagnosed with cervical cancer every minute. Early diagnosis and classification of cervical lesions greatly boosts up the chance of successful treatments of pati...
A fuzzy rank-based ensemble of CNN models for classification of cervical cytology.
Scientific reports
Jul 15, 2021
Cervical cancer affects more than 0.5 million women annually causing more than 0.3 million deaths. Detection of cancer in its early stages is of prime importance for eradicating the disease from the patient's body. However, regular population-wise sc...
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