Classification of Cervical Precursor Lesions via Local Histogram and Cell Morphometric Features-Reference-Cited by-同舟云学术

Classification of Cervical Precursor Lesions via Local Histogram and Cell Morphometric Features

Published:2022 Issue: Volume: Page:1-11
ISSN:2168-2194
Container-title:IEEE Journal of Biomedical and Health Informatics
language:
Short-container-title:IEEE J. Biomed. Health Inform.

Author:

Calik Nurullah¹^ORCID,Albayrak Abdulkadir²^ORCID,Akhan Asli³,Turkmen Ilknur⁴,Capar Abdulkerim⁵,Toreyin Behcet Ugur⁵,Bilgin Gokhan⁶^ORCID,Muezzinoglu Bahar⁷,Durak-Ata Lutfiye⁵^ORCID

Affiliation:

1. Department of Biomedical Engineering, Istanbul Medeniyet University, Istanbul, Turkey

2. Department of Computer Engineering, Dicle University, Diyarbakir, Turkey

3. Department of Pathology, Selahaddin Eyyubi Hospital, Diyarbakir, Turkey

4. The Department of Pathology, Memorial Sisli Hospital, Istanbul, Turkey

5. Informatics Institute, Istanbul Technical University, Istan- bul, Turkey

6. Department of Computer Engineering, Yildiz Technical University, Istanbul, Turkey

7. Department of Pathology, Istanbul Medipol University, Istanbul, Turkey

Funder

Scientific Research Projects Coordination Department

Istanbul Technical University

Yildiz Technical University

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Health Information Management,Electrical and Electronic Engineering,Computer Science Applications,Health Informatics

Link

http://xplorestaging.ieee.org/ielx7/6221020/6363502/09933790.pdf?arnumber=9933790

Reference38 articles.

1. A dense multi-path decoder for tissue segmentation in histopathology images

2. A Hybrid Deep Learning and Handcrafted Feature Approach for Cervical Cancer Digital Histology Image Classification

3. Human Papillomavirus Infection and the Multistage Carcinogenesis of Cervical Cancer

4. Convolutional Neural Network Based Localized Classification of Uterine Cervical Cancer Digital Histology Images.

5. Feature-based registration of histopathology images with different stains: An application for computerized follicular lymphoma prognosis

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