Cytopathology plays a central role in the early detection of cancers such as cervical, lung, and bladder cancer due to its speed, simplicity, and minimally invasive nature. However, its effectiveness is limited by variability in diagnostic accuracy stemming from subjective visual interpretation. Although many AI-powered systems have been proposed to improve consistency, none have achieved fully autonomous, clinical-grade performance. Existing approaches serve as assistive tools and still rely on human oversight for interpretation and decision-making. Here we present a clinical-grade autonomous cytopathology pipeline that combines high-resolution, real-time optical whole-slide tomography with edge computing to deliver end-to-end automation. The system achieves practical performance in imaging speed, quality, and data volume, with localized data compression enabling streamlined storage and accelerated AI-driven analysis. In addition to supporting cell-level classification, the platform enables flow cytometry-like, population-wide morphological profiling for comprehensive interpretation of cellular distributions and patterns. A vision transformer achieved area-under-receiver-operating-characteristic-curve values exceeding 0.99 for detecting LSIL, HSIL, and adenocarcinoma. In a clinical cohort of cervical liquid-based cytology samples from 318 donors, LSIL counts strongly correlated with HPV positivity, while HSIL counts scaled with diagnostic severity. The system enables autonomous triage cytology, offering a foundation for routine, scalable, and objective diagnostics.

N. N., T. S., and K. G. are shareholders of CYBO. N. N., T. S., and K. G. are inventors of patents covering the data analysis and display method. N. N. and T. S. are inventors of patents and patent applications covering the 3D image compression and processing techniques. The other authors have no competing interests.

This work was supported by funding from the Tokyo Metropolitan Small and Medium Enterprise Support Center, the Japan Agency for Medical Research and Development (AMED; Grant Number: JP20he102202), the Ichimura Foundation for New Technology, and Koto City. We also acknowledge support from the Advanced Medical Device Acceleration Project of Tokyo Prefecture, as well as from NVIDIA Inception, Microsoft for Startups, AWS Startups, Google for Startups, and Serendipity Lab. We are grateful to Incubate Fund and JAFCO for their financial support.

I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.

Yes

The details of the IRB/oversight body that provided approval or exemption for the research described are given below:

We analyzed 770 cervical cytology samples, including 766 liquid-based cytology samples and 4 conventional smear samples, collected from 770 patients who underwent cervical cytology testing at the Cancer Institute Hospital of the Japanese Foundation for Cancer Research (JFCR) between 2011 and 2019. The study was approved by the Institutional Review Board of JFCR (IRB No. 2019-GA-1190) and conducted in accordance with the principles of the Declaration of Helsinki. Informed consent was obtained from all participants through an opt-out process.

I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.

Yes

I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).

Yes

I have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.

Yes

The cytology datasets analyzed in this study are securely maintained by CYBO to safeguard patient privacy and proprietary imaging data. Due to ethical and regulatory constraints, these datasets are not publicly available. Academic investigators with no relevant conflicts of interest may request access to selected cytological features for non-commercial, research-only purposes, subject to review and approval by both CYBO and the Cancer Institute Hospital of JFCR. All data recipients must agree not to redistribute the data. Requests should be directed to N.N. at nittacybo.co.jp. CYBO reserves the right to decline requests at its discretion and will respond within one month of receipt.