Computational cytology is a critical, rapid-developing, yet challenging topic in medical
image computing concerned with analyzing digitized cytology images by computer-aided …

Cytopathological examination plays a crucial role in cancer diagnosis as it reflects the
cellular pathology of cancer. However, this process traditionally relies on the visual …

Microscopic examination of urinary sediments is a common laboratory procedure.
Automated image-based classification of urinary sediments can reduce analysis time and …

Background Urine cytology, although a useful screening method for urothelial carcinoma,
lacks sensitivity. As an emerging technology, artificial intelligence (AI) improved image …

Background Urine cytology is generally considered the primary approach for screening for
recurrence of bladder cancer. However, it is currently unclear how best to use cytological …

Background Urine cytology is commonly used as a screening test for high‐grade urothelial
carcinoma for patients with risk factors or hematuria and is an essential step in longitudinal …

Background Urine cytology is an important non-invasive examination for urothelial
carcinoma (UC) diagnosis and follow-up. We aimed to explore whether artificial intelligence …

Deep learning technology has been used in the medical field to produce devices for clinical
practice. Deep learning methods in cytology offer the potential to enhance cancer screening …

Automated urine sediment analyzers play a crucial role in diagnosing urinary tract infections,
offering real-time data analysis and expediting patient diagnosis. This paper introduces a …

The practice of cytopathology has been significantly refined in recent years, largely through
the creation of consensus rule sets for the diagnosis of particular specimens (Bethesda …