A new deep convolutional neural network model for classifying breast cancer histopathological images and the hyperparameter optimisation of the proposed model

BURÇAK, KADİR CAN; Uğuz, Harun; Baykan, Ömer Kaan

doi:10.1007/s11227-020-03321-y

A new deep convolutional neural network model for classifying breast cancer histopathological images and the hyperparameter optimisation of the proposed model

Yazarlar
Dr. Öğr. Üyesi Kadir Can BURÇAK Kurum Bilgileri Kaman Uygulamalı Bilimler Yüksekokulu Bilişim Sistemleri ve Teknolojileri Bilişim Sistemleri ve Teknolojileri Özgeçmiş Sayfası İletişim Bilgileri: (000)000-0000 Türkiye
Harun Uğuz Konya Teknik Üniversitesi, Türkiye
Ömer Kaan Baykan Türkiye

Özet

Deep learning algorithms have yielded remarkable results in medical diagnosis and image analysis, besides their contribution to improvements in a number of fields such as drug discovery, time-series modelling and optimisation methods. With regard to the analysis of histopathologic breast cancer images, the similarity of those images and the presence of healthy and tumourous tissues in different areas complicate the detection and classification of tumours on whole slide images. An accurate diagnosis in a short time is a need for full treatment in breast cancer. A successful classification on breast cancer histopathological images will overcome the burden on the pathologist and reduce the subjectivity of diagnosis. In this study, we propose a deep convolutional neural network model. The model uses various algorithms (i.e., stochastic gradient descent, Nesterov accelerated gradient, adaptive gradient, RMSprop, AdaDelta and Adam) to compute the initial weight of the network and update the model parameters for faster backpropagation learning. In order to train the model with less hardware in a short time, we used the parallel computing architecture with Cuda-enabled graphics processing unit. The results indicate that the deep convolutional neural network model is an effective classification model with a high performance up to 99.05% accuracy value.

Anahtar Kelimeler

Deep learning | Convolutional neural network | Breast cancer | Histopathology | Image classification

Makale Türü	Özgün Makale
Makale Alt Türü	SSCI, AHCI, SCI, SCI-Exp dergilerinde yayımlanan tam makale
Dergi Adı	JOURNAL OF SUPERCOMPUTING
Dergi ISSN	0920-8542
Dergi Tarandığı Indeksler	SCI-Expanded
Dergi Grubu	Q2
Makale Dili	İngilizce
Basım Tarihi	01-2021
Cilt No	77
Sayı	1
Sayfalar	973 / 989
Doi Numarası	10.1007/s11227-020-03321-y
Makale Linki	http://dx.doi.org/10.1007/s11227-020-03321-y

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A new deep convolutional neural network model for classifying breast cancer histopathological images and the hyperparameter optimisation of the proposed model

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A new deep convolutional neural network model for classifying breast cancer histopathological images and the hyperparameter optimisation of the proposed model

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