This study includes investigating the presence of tumor regions in Magnetic Resonance Imaging (MRI) slices. Since the MRI taken from a patient consists of many slices, it may take time for experts to review these images. The aim of the study is to evaluate the specialist's MRI slices more quickly. The image of each MRI slice taken from the patient was applied to the Alexnet transfer learning algorithm and the properties of the image were obtained. These features are optimized with the Relieff feature selection algorithm to achieve optimum success. The highest accuracy has been achieved with the support vector machine classifier, in which optimized features are used. The study was validated with 3 different combinations by training with two datasets and testing with the other. Thus, a method that can work under different conditions were obtained. The performance metrics of the study were obtained by taking the average of the successes obtained from each data set. MRIs were trained with Alexnet transfer learning model and performance analysis was performed on the obtained classification models. The feature optimization used both increased the success to 97.55% and reduced the processing time from 0.4064 to 0.3045 seconds. The proposed model with a high success rate and a rapid classification is expected to assist the expert in both diagnosis and treatment planning.
Brain Magnetic Resonance Imaging, Feature Extraction with Alexnet Transfer Learning, Relieff Feature Selection, Support Vector Machines
Birincil Dil | İngilizce |
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Konular | Mühendislik |
Yayınlanma Tarihi | December 2020 |
Bölüm | Research Article |
Yazarlar |
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Yayımlanma Tarihi | 30 Aralık 2020 |
Başvuru Tarihi | 3 Kasım 2020 |
Kabul Tarihi | 29 Aralık 2020 |
Yayınlandığı Sayı | Yıl 2020, Cilt 4, Sayı 2 |
Bibtex | @araştırma makalesi { asujse820599, journal = {Aksaray University Journal of Science and Engineering}, issn = {}, eissn = {2587-1277}, address = {Aksaray Üniversitesi, Fen Bilimleri Enstitüsü, Merkez Kampüs, 68100 Aksaray}, publisher = {Aksaray Üniversitesi}, year = {2020}, volume = {4}, pages = {187 - 198}, doi = {10.29002/asujse.820599}, title = {Detection of Tumor Slice in Brain Magnetic Resonance Images by Feature Optimized Transfer Learning}, key = {cite}, author = {Çelik, Salih} } |
APA | Kasım, Ö. & Çelik, S. (2020). Detection of Tumor Slice in Brain Magnetic Resonance Images by Feature Optimized Transfer Learning . Aksaray University Journal of Science and Engineering , 4 (2) , 187-198 . DOI: 10.29002/asujse.820599 |
MLA | Kasım, Ö. , Çelik, S. "Detection of Tumor Slice in Brain Magnetic Resonance Images by Feature Optimized Transfer Learning" . Aksaray University Journal of Science and Engineering 4 (2020 ): 187-198 <http://asujse.aksaray.edu.tr/tr/pub/issue/58393/820599> |
Chicago | Kasım, Ö. , Çelik, S. "Detection of Tumor Slice in Brain Magnetic Resonance Images by Feature Optimized Transfer Learning". Aksaray University Journal of Science and Engineering 4 (2020 ): 187-198 |
RIS | TY - JOUR T1 - Detection of Tumor Slice in Brain Magnetic Resonance Images by Feature Optimized Transfer Learning AU - Ömer Kasım , Salih Çelik Y1 - 2020 PY - 2020 N1 - doi: 10.29002/asujse.820599 DO - 10.29002/asujse.820599 T2 - Aksaray University Journal of Science and Engineering JF - Journal JO - JOR SP - 187 EP - 198 VL - 4 IS - 2 SN - -2587-1277 M3 - doi: 10.29002/asujse.820599 UR - https://doi.org/10.29002/asujse.820599 Y2 - 2020 ER - |
EndNote | %0 Aksaray University Journal of Science and Engineering Detection of Tumor Slice in Brain Magnetic Resonance Images by Feature Optimized Transfer Learning %A Ömer Kasım , Salih Çelik %T Detection of Tumor Slice in Brain Magnetic Resonance Images by Feature Optimized Transfer Learning %D 2020 %J Aksaray University Journal of Science and Engineering %P -2587-1277 %V 4 %N 2 %R doi: 10.29002/asujse.820599 %U 10.29002/asujse.820599 |
ISNAD | Kasım, Ömer , Çelik, Salih . "Detection of Tumor Slice in Brain Magnetic Resonance Images by Feature Optimized Transfer Learning". Aksaray University Journal of Science and Engineering 4 / 2 (Aralık 2020): 187-198 . https://doi.org/10.29002/asujse.820599 |
AMA | Kasım Ö. , Çelik S. Detection of Tumor Slice in Brain Magnetic Resonance Images by Feature Optimized Transfer Learning. Aksaray J. Sci. Eng.. 2020; 4(2): 187-198. |
Vancouver | Kasım Ö. , Çelik S. Detection of Tumor Slice in Brain Magnetic Resonance Images by Feature Optimized Transfer Learning. Aksaray University Journal of Science and Engineering. 2020; 4(2): 187-198. |
IEEE | Ö. Kasım ve S. Çelik , "Detection of Tumor Slice in Brain Magnetic Resonance Images by Feature Optimized Transfer Learning", Aksaray University Journal of Science and Engineering, c. 4, sayı. 2, ss. 187-198, Ara. 2020, doi:10.29002/asujse.820599 |
Aksaray J. Sci. Eng. | e-ISSN: 2587-1277 | Period: Biannually | Founded: 2017 | Publisher: Aksaray University | https://asujse.aksaray.edu.tr
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