Dual supervised sampling networks for real-time segmentation of cervical cell nucleus

Luo, Die; Kang, Huifang; Long, Junan; Zhang, Jun; Chen, Li; Quan, Tingwei; Liu, Xiuli

doi:10.1016/j.csbj.2022.08.023

Cited by 9 publications

(1 citation statement)

References 42 publications

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“…Luo et al [126] proposed a dual-supervised sampling network (DSSNet) to accelerate the speed of cervical nucleus segmentation, as illustrated in Fig. 15.…”

Section: Segmentation Of Nucleus and Cytoplasmmentioning

confidence: 99%

A Survey on Deep Learning-based Cervical Cytology Screening: from Cell Identification to Whole Slide Image Analysis

Jiang

Shen

et al. 2023

Preprint

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Cervical cancer is one of the most common cancers in daily life. Early detection and diagnosis can effectively help facilitate subsequent clinical treatment and management. With the growing advancement of artificial intelligence (AI) and deep learning (DL) techniques, an increasing number of computer-aided diagnosis (CAD) methods based on deep learning have been applied in cervical cytology screening. In this paper, we survey more than 70 publications since 2016 to provide a systematic and comprehensive review of DL-based cervical cytology screening. First, we provide a concise summary of the medical and biological knowledge pertaining to cervical cytology, since we hold a firm belief that a comprehensive biomedical understanding can significantly contribute to the development of CAD systems. Then, we collect a wide range of public cervical cytology datasets. Besides, image analysis approaches and applications including cervical cell identification, abnormal cell or area detection, cell region segmentation and cervical whole slide image diagnosis are summarized. Finally, we discuss the present obstacles and promising directions for future researches in automated cervical cytology screening.

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“…Luo et al [126] proposed a dual-supervised sampling network (DSSNet) to accelerate the speed of cervical nucleus segmentation, as illustrated in Fig. 15.…”

Section: Segmentation Of Nucleus and Cytoplasmmentioning

confidence: 99%

A Survey on Deep Learning-based Cervical Cytology Screening: from Cell Identification to Whole Slide Image Analysis

Jiang

Shen

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

A systematic review of deep learning-based cervical cytology screening: from cell identification to whole slide image analysis

Jiang,

Li,

Shen

et al. 2023

Artif Intell Rev

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Cervical cancer is one of the most common cancers in daily life. Early detection and diagnosis can effectively help facilitate subsequent clinical treatment and management. With the growing advancement of artificial intelligence (AI) and deep learning (DL) techniques, an increasing number of computer-aided diagnosis (CAD) methods based on deep learning have been applied in cervical cytology screening. In this paper, we survey more than 80 publications since 2016 to provide a systematic and comprehensive review of DL-based cervical cytology screening. First, we provide a concise summary of the medical and biological knowledge pertaining to cervical cytology, since we hold a firm belief that a comprehensive biomedical understanding can significantly contribute to the development of CAD systems. Then, we collect a wide range of public cervical cytology datasets. Besides, image analysis approaches and applications including cervical cell identification, abnormal cell or area detection, cell region segmentation and cervical whole slide image diagnosis are summarized. Finally, we discuss the present obstacles and promising directions for future research in automated cervical cytology screening.

show abstract

Review of cervical cell segmentation

Huang,

Zhang,

Chen

et al. 2024

Multimed Tools Appl

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Dual supervised sampling networks for real-time segmentation of cervical cell nucleus

Cited by 9 publications

References 42 publications

A Survey on Deep Learning-based Cervical Cytology Screening: from Cell Identification to Whole Slide Image Analysis

A Survey on Deep Learning-based Cervical Cytology Screening: from Cell Identification to Whole Slide Image Analysis

A systematic review of deep learning-based cervical cytology screening: from cell identification to whole slide image analysis

Review of cervical cell segmentation

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