Automatic Cervical Cell Classification Using Patch-Based Fuzzy Clustering and Minimum Average Correlation Energy Filter

Chankong, Thanatip; Theera-Umpon, Nipon; Auephanwiriyakul, Sansanee

doi:10.1007/978-3-319-02913-9_42

Cited by 3 publications

(1 citation statement)

References 5 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In the state-of-the-art, much effort is dedicated to recognise the cell nucleus since it is a key part for determining biological structures. Previously, the computer-aided recognition of cell nuclei has been addressed using different techniques such as clustering (Gharipour and Liew, 2015;Chankong et al, 2014;Kothari et al, 2009), segmentation (Mohammed et al, 2013;Palacios and Beltran, 2007;Rogojanu et al, 2010) adaptive active contour (Kang et al, 2015;Hafiane et al, 2008;Zeng et al, 2013), and machine learning (Kancherla and Mukkamala, 2013;Han et al, 2012b;Shir et al, 2007).…”

Section: Recognition Of Fundamental Tissuesmentioning

confidence: 99%

Automatic classification of histological images and histological knowledge modelling of the human cardivascular system = Clasificación automática de imágenes histológicas y modelado del conocimiento histológico del sistema cardiovascular humano

Vargas¹,

Ximena²

View full text Add to dashboard Cite

Section: Recognition Of Fundamental Tissuesmentioning

confidence: 99%

Automatic classification of histological images and histological knowledge modelling of the human cardivascular system = Clasificación automática de imágenes histológicas y modelado del conocimiento histológico del sistema cardiovascular humano

Vargas¹,

Ximena²

View full text Add to dashboard Cite

Segmentation Of Pap Smear Images For Cervical Cancer Detection

Bandyopadhyay

Nasipuri

2020

2020 IEEE Calcutta Conference (CALCON)

View full text Add to dashboard Cite

Cytology Image Analysis Techniques Toward Automation

et al. 2021

View full text Add to dashboard Cite

Cytology is a branch of pathology that deals with the microscopic examination of cells for diagnosis of carcinoma or inflammatory conditions. In the present work, the term cytology is used to indicate solid organ cytology. Automation in cytology started in the early 1950s with an aim to reduce manual efforts in the diagnosis of cancer. The influx of intelligent systems with high computational power and improved specimen collection techniques helped to achieve technological heights in the cytology automation process. In the present survey, we focus on image analysis techniques paving the way to automation in cytology. We take a short tour of 17 types of solid organ cytology to explore various segmentation and/or classification techniques that evolved during the past three decades to automate cytology image analysis. It is observed that most of the works are aligned toward three types of cytology: Cervical, Breast, and Respiratory tract cytology. These are discussed elaborately in the article. Commercial systems developed during the period are also summarized to comprehend the overall growth in respective domains. Finally, we discuss different state-of-the-art methods and related challenges to provide prolific and competent future research directions in bringing cytology-based commercial systems into the mainstream.

show abstract

Automatic Cervical Cell Classification Using Patch-Based Fuzzy Clustering and Minimum Average Correlation Energy Filter

Cited by 3 publications

References 5 publications

Automatic classification of histological images and histological knowledge modelling of the human cardivascular system = Clasificación automática de imágenes histológicas y modelado del conocimiento histológico del sistema cardiovascular humano

Automatic classification of histological images and histological knowledge modelling of the human cardivascular system = Clasificación automática de imágenes histológicas y modelado del conocimiento histológico del sistema cardiovascular humano

Segmentation Of Pap Smear Images For Cervical Cancer Detection

Cytology Image Analysis Techniques Toward Automation

Contact Info

Product

Resources

About