Recent CNN-based techniques for breast cancer histology image classification

العناوين الأخرى

التقنيات الحديثة المعتمدة على شبكة CNN لتصنيف صور سرطان الثدي

المؤلفون المشاركون

Karuppasamy, Aruna Devi
Abd al-Salam, Abd al-Hamid
Hajjam, Rashid
Zaydum, Hamzah
al-Bahri, Mayya

المصدر

The Journal of Engineering Research

العدد

المجلد 19، العدد 1 (30 يونيو/حزيران 2022)، ص ص. 41-53، 13ص.

الناشر

جامعة السلطان قابوس كلية الهندسة

تاريخ النشر

2022-06-30

دولة النشر

سلطنة عمان

عدد الصفحات

13

التخصصات الرئيسية

هندسة مدنية
تكنولوجيا المعلومات وعلم الحاسوب

الملخص EN

Histology images are extensively used by pathologists to assess abnormalities and detect malignancy in breast tissues.

On the other hand, Convolutional Neural Networks (CNN) are by far, the privileged models for image classification and interpretation.

Based on these two facts, we surveyed the recent CNN-based methods for breast cancer histology image analysis.

The survey focuses on two major issues usually faced by CNN-based methods namely the design of an appropriate CNN architecture and the lack of a sufficient labelled dataset for training the model.

Regarding the design of the CNN architecture, methods examining breast histology images adopt three main approaches: Designing manually from scratch the CNN architecture, using pre-trained models and adopting an automatic architecture design.

Methods addressing the lack of labelled datasets are grouped into four categories: methods using pre-trained models, methods using data augmentation, methods adopting weakly supervised learning and those adopting feedforward filter learning.

Research works from each category and reported performance are presented in this paper.

We conclude the paper by indicating some future research directions related to the analysis of histology images.

نمط استشهاد جمعية علماء النفس الأمريكية (APA)

Karuppasamy, Aruna Devi& Abd al-Salam, Abd al-Hamid& Hajjam, Rashid& Zaydum, Hamzah& al-Bahri, Mayya. 2022. Recent CNN-based techniques for breast cancer histology image classification. The Journal of Engineering Research،Vol. 19, no. 1, pp.41-53.
https://search.emarefa.net/detail/BIM-1341178

نمط استشهاد الجمعية الأمريكية للغات الحديثة (MLA)

Karuppasamy, Aruna Devi…[et al.]. Recent CNN-based techniques for breast cancer histology image classification. The Journal of Engineering Research Vol. 19, no. 1 (2022), pp.41-53.
https://search.emarefa.net/detail/BIM-1341178

نمط استشهاد الجمعية الطبية الأمريكية (AMA)

Karuppasamy, Aruna Devi& Abd al-Salam, Abd al-Hamid& Hajjam, Rashid& Zaydum, Hamzah& al-Bahri, Mayya. Recent CNN-based techniques for breast cancer histology image classification. The Journal of Engineering Research. 2022. Vol. 19, no. 1, pp.41-53.
https://search.emarefa.net/detail/BIM-1341178

نوع البيانات

مقالات

لغة النص

الإنجليزية

الملاحظات

Includes bibliographical references : p. 51-53

رقم السجل

BIM-1341178