| Yazarlar (3) |
Dr. Öğr. Üyesi Fatih UYSAL
Kafkas Üniversitesi |
|
Firat Hardalac
|
|
Mustafa Koc
|
| Özet |
| Prostate cancer is a type of cancer that is very common in men. Literature review, it has been observed that there are many studies conducted on this prostate image using various image processing methods for cancer diagnosis and treatment. Secondary hemorrhage sites in prostate biopsy may cause misdiagnosis in T2-weighted magnetic resonance (MR) prostate images, in terms of tumor. In these cases, T1-weighted MR imaging of the prostate is helpful in diagnosing. In such situations, it may be helpful to prevent misdiagnosis and to help diagnosis; In this study, one deep convolutional neural network learning algorithms (CNN) using T1 and T2-weighted MR image classification process of the prostate were performed. As a result of this, an CNN model was developed that can classify MR prostate images. |
| Anahtar Kelimeler |
| deep learning | convolutional neural networks | image classification | magnetic resonance prostate images |
| Makale Türü | Özgün Makale |
| Makale Alt Türü | Uluslararası alan indekslerindeki dergilerde yayınlanan tam makale |
| Dergi Adı | 2018 MEDICAL TECHNOLOGIES NATIONAL CONGRESS (TIPTEKNO) |
| Makale Dili | İngilizce |
| Basım Tarihi | 01-2018 |
