Deep learning based brain tumor classification and detection system

Ali ARI; Davut HANBAY

Makale detayları

Deep learning based brain tumor classification and detection system

Yazarlar:

Ali ARI | Davut HANBAY

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Electrical Engineering and Computer Science 2018 Vol.26 Issue 5, pp.2275-2286

Belge Tipi:

Makale

Yayın Tarihi:

9/2018

Belge Dili:

Türkçe

Document ID (Org No.):

2000734692

Sıklık:

İki Aylık

eISSN:

1303-6203

pISSN:

1300-0632

Özet:

 

The brain cancer treatment process depends on the   physician's experience and knowledge. For this reason, using an automated   tumor detection system is extremely important to aid radiologists and   physicians to detect brain tumors. The proposed method has three stages,   which are preprocessing, the extreme learning machine local receptive fields   (ELM-LRF) based tumor classification, and image processing based tumor   region extraction. At first, nonlocal means and local smoothing methods were   used to remove possible noises. In the second stage, cranial   magnetic resonance (MR) images were classified as benign or malignant by   using ELM-LRF. In the third stage, the tumors were segmented. The purpose of   the study was using only cranial MR images, which have a mass, in order to   save the physician's time. In the experimental studies the classification   accuracy of cranial MR images is 97.18 %. Evaluated results showed that   the proposed method's performance was better than the other recent studies   in the literature. Experimental results also proved that the proposed method   is effective and can be used in computer aided brain tumor detection.

Makale detayları

Deep learning based brain tumor classification and detection system

Yazarlar: Ali ARI | Davut HANBAY

Yayıncı: TUBITAK

Dergi: Turkish Journal of Electrical Engineering and Computer Science 2018 Vol.26 Issue 5, pp.2275-2286

Belge Tipi: Makale

Yayın Tarihi: 9/2018

Belge Dili: Türkçe

Document ID (Org No.): 2000734692

Sıklık: İki Aylık

eISSN: 1303-6203

pISSN: 1300-0632

Sayı

Yazarlar:

Ali ARI | Davut HANBAY

Yayıncı:

TUBITAK

Dergi:

Turkish Journal of Electrical Engineering and Computer Science 2018 Vol.26 Issue 5, pp.2275-2286

Belge Tipi:

Makale

Yayın Tarihi:

9/2018

Belge Dili:

Türkçe

Document ID (Org No.):

2000734692

Sıklık:

İki Aylık

eISSN:

1303-6203

pISSN:

1300-0632