DeepMitosis: Mitosis detection via deep detection, verification and segmentation networks

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Artificial intelligence for digital and computational pathology (2023, background): “…formulated as a subtyping problem, in which an algorithm aims to classify cases within a group of diagnoses; for example, classifying lymph nodes based on the binary presence or absence of metastases or identifying cases of non-small-cell lung cancer as adenocarcinoma or squamous cell carcinoma.”
Predicting breast tumor proliferation from whole‐slide images: The TUPAC16 challenge (2018, background): “Mitosis detection in WSIs is an active field of research ( Albarqouni et al., 2016; Chen et al., 2016a, 2016b; Li et al., 2018; Tellez et al., 2018a, 2018b ).”
The impact of pre- and post-image processing techniques on deep learning frameworks: A comprehensive review for digital pathology image analysis (2020, methodology): “Rao et al. [171] and Li et al. [172] proposed a modified version of the FASTER-RCNN tuned for mitosis detection, with comparable speed of previous CNN models and more accurate localization.”