DOAJ Open Access 2019

Deep Learning for Breast Cancer Diagnosis from Mammograms—A Comparative Study

Lazaros Tsochatzidis Lena Costaridou Ioannis Pratikakis

Lihat Sumber DOI

Abstrak

Deep convolutional neural networks (CNNs) are investigated in the context of computer-aided diagnosis (CADx) of breast cancer. State-of-the-art CNNs are trained and evaluated on two mammographic datasets, consisting of ROIs depicting benign or malignant mass lesions. The performance evaluation of each examined network is addressed in two training scenarios: the first involves initializing the network with pre-trained weights, while for the second the networks are initialized in a random fashion. Extensive experimental results show the superior performance achieved in the case of fine-tuning a pretrained network compared to training from scratch.

Topik & Kata Kunci

Photography Computer applications to medicine. Medical informatics Electronic computers. Computer science

Penulis (3)

Lazaros Tsochatzidis

Lena Costaridou

Ioannis Pratikakis

Format Sitasi

APA MLA BibTeX

Tsochatzidis, L., Costaridou, L., Pratikakis, I. (2019). Deep Learning for Breast Cancer Diagnosis from Mammograms—A Comparative Study. https://doi.org/10.3390/jimaging5030037

Akses Cepat

Lihat di Sumber doi.org/10.3390/jimaging5030037

Informasi Jurnal

Tahun Terbit: 2019
Sumber Database: DOAJ
DOI: 10.3390/jimaging5030037
Akses: Open Access ✓