ArticleScientific data2021
Cric searchable image database as a public platform for conventional pap smear cytology data.
Article in Scientific data, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers.
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Who cites it
20 citing papers in PubMed, 61 citations in OpenAlex.
- Uncertainty-aware and interpretable deep learning in cytopathology: toward trustworthy AI-powered diagnostics.Virchows Archiv : an international journal of pathology · 2026Review
- Supporting the Learning of Visual Perception Skills in Cytology Through a Computational Tool: Development and Evaluation Study.JMIR formative research · 2026Article
- AI for cervical cancer screening on whole slide images: opportunities with open-source simple tools.Pathologica · 2026Article
- Robust Cell-Level Classification for Liquid-Based Cervical Cytology Using Deep Transfer Learning: A Multi-Source Study Addressing Scanner-Induced Domain Shifts.Bioengineering (Basel, Switzerland) · 2026Article
- Artificial intelligence for colposcopic and cytological image analysis in early cervical cancer detection.iScience · 2026Review
- Pre-analytical reporting in AI-assisted cervical cytology: a scoping review of data acquisition documentation.Frontiers in artificial intelligence · 2026Review
- Diagnostic accuracy of an artificial intelligence-driven cytopathological tool in detecting cervical pre-cancerous lesions from Pap smear images.Frontiers in digital health · 2026Article
- Dataset of multi-focus (Z-stack) images derived from liquid-based cervical cancer cytology specimens.F1000Research · 2026Article
- RIVA: An Image Dataset of Conventional Pap Smear Cytology with Multiple Independent Annotations.Scientific data · 2025Article
- NLTD 2.0: A Nonlinear Framework for Robust and Customizable Color Deconvolution in Histopathology.bioRxiv : the preprint server for biology · 2025Article
- Synthetic Scientific Image Generation with VAE, GAN, and Diffusion Model Architectures.Journal of imaging · 2025Article
- BMT: A Cross-Validated ThinPrep Pap Cervical Cytology Dataset for Machine Learning Model Training and Validation.Scientific data · 2024Article
- Automated Screening of Precancerous Cervical Cells Through Contrastive Self-Supervised Learning.Life (Basel, Switzerland) · 2024Article
- Annotated Pap cell images and smear slices for cell classification.Scientific data · 2024Article
- Pixel-wise segmentation of cells in digitized Pap smear images.Scientific data · 2024Article
- Toward Interpretable Cell Image Representation and Abnormality Scoring for Cervical Cancer Screening Using Pap Smears.Bioengineering (Basel, Switzerland) · 2024Article
- CerviCell-detector: An object detection approach for identifying the cancerous cells in pap smear images of cervical cancer.Heliyon · 2023Article
- Automated cervical cell segmentation using deep ensemble learning.BMC medical imaging · 2023Article
- Detection of Cervical Cancer Cells in Whole Slide Images Using Deformable and Global Context Aware Faster RCNN-FPN.Current oncology (Toronto, Ont.) · 2021Article
- A Deep Learning Ensemble Method to Assist Cytopathologists in Pap Test Image Classification.Journal of imaging · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Amidst the current health crisis and social distancing, telemedicine has become an important part of mainstream of healthcare, and building and deploying computational tools to support screening more efficiently is an increasing medical priority. The early identification of cervical cancer precursor lesions by Pap smear test can identify candidates for subsequent treatment. However, one of the main challenges is the accuracy of the conventional method, often subject to high rates of false negative. While machine learning has been highlighted to reduce the limitations of the test, the absence of high-quality curated datasets has prevented strategies development to improve cervical cancer screening. The Center for Recognition and Inspection of Cells (CRIC) platform enables the creation of CRIC Cervix collection, currently with 400 images (1,376 × 1,020 pixels) curated from conventional Pap smears, with manual classification of 11,534 cells. This collection has the potential to advance current efforts in training and testing machine learning algorithms for the automation of tasks as part of the cytopathological analysis in the routine work of laboratories.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.