Enhanced Cellular Detection in Cervical Cytopathology: A Systematic Study of YOLO11 Training Paradigms

Automated cellular detection using deep learning is a key strategy for optimising cervical cancer screening by reducing the healthcare workload and inter-observer variability. However, analysing Whole Slide Image (WSI) patches presents challenges such as annotation scarcity, morphological complexity...

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Detalles Bibliográficos

Principais autores:	Sandra Marcos-Recio, Andrés Barrero-Bueno, Lautaro Rossi-Labianca, Ana Belén Gil-González, Andrés Cardona-Mendoza, Sandra Janneth Perdomo-Lara
Formato:	Artigo
Idioma:	Inglês
Publicado:	MDPI AG 2026-05-01
Series:	Applied Sciences
Assuntos:	cervical cytology artificial intelligence instance detection YOLO11 deep learning single class
Acceso en liña:	https://www.mdpi.com/2076-3417/16/9/4464
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