Automatic detection of cancer metastasis in lymph node using deep learning
Yükleniyor...
Tarih
2023
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Elsevier
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Lymph node metastases are one of the most indicator of some cancer types such as breast, colon and prostate.
Breast cancer mostly spreads to lymph nodes in the armpit and it is one of the most common causes of death in
women worldwide. Pathologists need more attention and time to diagnose metastasis in digitized lymph node
images and also this process tends to be misinterpreted. In this paper, a promising deep learning based approach
was presented to detect cancer metastasis in lymph node images with higher accuracy. The proposed deep
learning framework uses ResNet architectures, transfer learning and 1cycle policy which is the method of finding
the optimal learning rate. The validity of the proposed approach was evaluated on PCAM dataset consisted of
220,025 lymph node images. The experiments demonstrated that the presented method outperformed most of
the current studies, achieving accuracy of 98.60% on the PCAM dataset by using ResNet models and fine-tuning
techniques effectively. The burden of diagnosis procedure of metastasis can be lessened with the proposed deep
learning framework in the clinical applications.
Açıklama
Anahtar Kelimeler
Deep learning, Convolutional neural network, Lymph node metastasis, Cancer detection
Kaynak
Biomedical Signal Processing and Control
WoS Q Değeri
Q2
Scopus Q Değeri
Q1
Cilt
Sayı
82
Künye
Bütün, E., Uçan, M. ve Kaya, M. (2023). Automatic detection of cancer metastasis in lymph node using deep learning. Biomedical Signal Processing and Control, (82), 1-8.
