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16. A novel study to increase the classification parameters on automatic three-class COVID-19 classification from CT images, including cases from Turkey.

Author

Yaşar, Hüseyin, Ceylan, Murat, Cebeci, Hakan, Kılınçer, Abidin, Kanat, Fikret, and Koplay, Mustafa

Subjects
DEEP learning, CONVOLUTIONAL neural networks, AUTOMATIC classification, RECEIVER operating characteristic curves, COVID-19, COMPUTED tomography
Abstract

A computed tomography (CT) scan is an important radiological imaging method in diagnosing pneumonia caused by SARS-CoV-2. Within the scope of the study, three classes of automatic classification – COVID-19 pneumonia, healthy, and other pneumonia – were carried out. Using deep learning as a classifier, a total of 6,377 CT images were used, including 3,364 COVID-19 pneumonia, 1,766 healthy, and 1,247 other pneumonia images. A total of seven architectures, including the most recent convolutional neural network (CNN) architectures, MobileNetV2, ResNet-101, Xception, Inceptionv3, GoogLeNet, EfficientNetB0, and DenseNet201, were used in the study. The classification results were obtained using the CT images, and they were calculated using the feature images obtained by applying local binary patterns on the CT images. The results were then combined with the help of a pipeline algorithm. The results revealed that the best overall accuracy result obtained by using CNN architectures could be improved by 4.87% with a two-step pipeline algorithm. In addition, significant improvements were achieved in all other measurement parameters within the scope of the study. At the end of the study, the highest sensitivity, specificity, accuracy, F-1 score, and Area under the Receiver Operating Characteristic Curve (AUC) values obtained for the COVID-19 pneumonia class were 0.9004, 0.8901, 0.8956, 0.9010, and 0.9600, respectively. The highest overall accuracy value was 0.8332. The most important output of the work carried out is the demonstration that the results obtained with the most successful CNN architectures used in previous studies can be significantly improved thanks to pipeline algorithms. [ABSTRACT FROM AUTHOR]

Published
2024
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17. Comparison of Diagnostic Performance of PI-RADS V2 and V2.1 and Interobserver Agreement in Both Versions.

Author

Baytok, Ahmet, Koplay, Mustafa, Özer, Halil, Topaloğlu, Ömer Faruk, Kaynar, Mehmet, Göktaş, Serdar, and Batur, Ali Furkan

Abstract

Objective: To compare the diagnostic performance for the detection of clinically significant prostate cancers and interobserver agreement between PI-RADS v2 and v2.1 Material and Method: The mpMRI images of 258 patients and 394 nodüles included in this retrospective study were obtained on 3T MR and evaluated by two radiologists according to PIRADS v2 and v2.1. Sensitivity and specificity between v2 and v2.1 were compared. Detection rates for clinically significant prostate cancers were evaluated. Interobserver agreement was evaluated using κ statistics. Results: PI-RADS v2.1 and v2 had higher sensitivity and lower specificity (100%, 52.38%) in the peripheral zone, and showed higher sensitivity and specificity (92.86%, 98.79%) in the transition zone for category ≥4 lesions to estimate csPCa, but no remarkable difference was found between the two versions. Interobserver agreement was statistically significant and very weak in the transition zone (κ=0.383, κ=0.279, respectively), very strong in the peripheral zone (κ=0.869) according to both classifications and they were similar. Conclusion: The diagnostic performance of PI-RADS v2 and v2.1 were found similar in the determination of clinically significant cancers and all cancers in both zones. The clinically significant cancer detection rate in category 2+1 lesions in the transition zone was higher than in category 2 lesions but it was not statistically significant. Interobserver agreement was low in the transition zone and very strong in the peripheral zone in both versions. [ABSTRACT FROM AUTHOR]

Published
2024
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22. Adrenal Lesion Classification on T1-Weighted Abdomen Images with Convolutional Neural Networks

Author

SOLAK, Ahmet, CEYLAN, Rahime, BOZKURT, Mustafa Alper, CEBECİ, Hakan, and KOPLAY, Mustafa

Subjects
Engineering, Electrical and Electronic, Abdomen, Adrenal Lesion, Classification, Convolutional Neural Network, Deep Learning, Magnetic Resonance, General Materials Science, Mühendislik, Elektrik ve Elektronik
Abstract

Adrenal lesions are usually discovered incidentally during other health screenings and are usually benign. However, it is vital to take precautions when a malignant adrenal lesion is detected. Especially deep learning models developed in the last ten years give successful results on medical images. In this paper, adrenal lesion characterization on T1-weighted magnetic resonance abdomen images was aimed using convolutional neural network (CNN) which is one of the deep learning methods. Firstly, effects of important model parameters are assessed on performance of CNN, so optimum CNN model is obtained for classification of adrenal lesions. For a fixed number of convolution filters determined in the first stage of the study, CNN model implemented by different kernel sizes were trained. According to the best result obtained, this time the kernel size was kept constant, and experiments were made for different filter numbers. Finally, studies were carried out with CNN structures of different depths and the results were compared. As a result of the studies, when filter is selected as [5 20], the best results in the trainings conducted with a single-block CNN structure are obtained 0.97, 0.90, 0.98, 0.90, 0.90, and 0.94, for accuracy, sensitivity, specificity, precision, F1-score, and AUC score, respectively. The study was compared with the studies in the literature, and it was seen that it was superior to them.

Published
2022

23. Adrenal Tumor Segmentation on U-Net: A Study About Effect of Different Parameters in Deep Learning.

Author

Solak, Ahmet, Ceylan, Rahime, Bozkurt, Mustafa Alper, Cebeci, Hakan, and Koplay, Mustafa

Subjects
ADRENAL tumors, TUMOR diagnosis, DEEP learning, IMAGE segmentation, DISCRETE wavelet transforms
Abstract

Adrenal lesions refer to abnormalities or growths that occur in the adrenal glands, which are located on top of each kidney. These lesions can be benign or malignant and can affect the function of the adrenal glands. This paper presents a study on adrenal tumor segmentation using a modified U-Net model with various parameter selection strategies. The study investigates the effect of fine-tuning parameters, including k-fold values and batch sizes, on segmentation performance. Additionally, the study evaluates the effectiveness of different preprocessing techniques, such as Discrete Wavelet Transform (DWT), Contrast Limited Adaptive Histogram Equalization (CLAHE), and Image Fusion, in enhancing segmentation accuracy. The results show that the proposed model outperforms the original U-Net model, achieving the highest scores for Dice, Jaccard, sensitivity, and specificity scores of 0.631, 0.533, 0.579, and 0.998, respectively, on the T1-weighted dataset with DWT applied. These results highlight the importance of parameter selection and preprocessing techniques in improving the accuracy of adrenal tumor segmentation using deep learning. [ABSTRACT FROM AUTHOR]

Published
2024
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30. Morphometric analysis of orbit in Turkish population: a MDCT study

Author

PİRİNÇ, Büşra, FAZLIOĞULLARI, Zeliha, KOPLAY, Mustafa, KARABULUT, Ahmet Kağan, and ÜNVER DOĞAN, Nadire

Subjects
Anatomi, morfometri, çok kesitli bilgisayarlı tomografi, orbita, Medicine, Anatomy, morphometry, multislice computed tomography, orbit, Tıp
Abstract

Amaç: Orbita bağlantı sağladıkları boşluklar, komşu olduğu bölgeler ve içerdiği yapılar sebebiyle oldukça önemli bir bölgedir. Çalışmamızda Türk popülasyonunun orbita morfometrisini, çok kesitli bilgisayarlı tomografi (ÇKBT) görüntülerinde cinsiyete, vücut tarafına göre farklılıklarını, yaşa bağlı gelişimini değerlendirmeyi amaçladık.Gereç ve Yöntem: 94’ü erkek, 106’sı kadın olmak üzere toplam 200 bireyin (400 taraf) ÇKBT görüntüleri üzerinde ölçümler yapıldı. Görüntüler cinsiyet, vücut tarafı ve anatomik yapıların gelişimlerine göre değerlendirildi.Bulgular: Sağlıklı bireylerde orbita yüksekliği, genişliği ve derinliği sırasıyla sağ tarafta ortalama 36,04±2,97 mm, 32,33±2,59 mm, 38,35±3,32 mm iken sol tarafta 35,79±3,18 mm, 32,29±2,67 mm, 38,13±3,21 mm olarak belirlendi. Orbita’nın yüksekliği ve genişliği her iki tarafta da erkeklerde kadınlardan istatistiksel olarak anlamlı derecede büyük olduğu tespit edildi (p˂0,05).Sonuç: Orbita ve ilişkili açıklıklar hakkında kapsamlı bilgi, ilgili bölgede çalışan klinisyenler açısından oldukça önemlidir, bu yapıların zarar görmesi ciddi komplikasyonlara neden olabilir. Bununla birlikte, orbita’nın morfometrisi adli tıpta cinsiyet, yaş ve ırk tespiti için önemli bir parametre olarak kullanılabilir., Objective: The orbit is an important cavity containing vision-related formations and important neurovascular structures, and adjacent to various regions. This study aimed to evaluation, by multidedector computed tomography (MDCT) images, the morphometry of orbit by examining its changes according to gender and body side, and developments according to age, in Turkish population.Materials and Methods: A total of 200 individuals’s (94 females,106 males;400 sides) MDCT images were evaluated. Images were examined according to the gender, body side, and the anatomical structures development.Results: The height, width and depth of the orbit were determined as 36.04±2.97 mm, 32.33±2.59 mm, 38.35±3.32 mm on the right side, 35.79±3.18 mm, 32.29±2.67 mm, 38.13±3.21 mm on the left side, respectively, in healthy subjects. The height and width of the orbit were found to be statistically significantly larger on both sides in men than in women (p˂0.05). Conclusion: Comprehensive information about the orbit and associated apertures is quite important for clinicians working in this area, damage to these structures can cause serious complications. In addition, determining the morphometry of the orbit can be used as an important parameter for determining gender, age and race in forensic medicine.

Published
2022

50. Poster presentations

Author

Aksu, Funda, Topacoglu, Hakan, Arman, Candan, Atac, Aytul, Tetik, Suleyman, Hasanovic, Aida, Kulenovic, Amela, Mornjakovic, Zakira, Pikula, Branko, Sarac-Hadzihalilovic, Aida, Voljevica, Alma, Bamac, Belgin, Colak, Tuncay, Alemdar, Murat, Dundar, Gulmine, Selekler, Macit, Dincer, Ozgur, Colak, Enis, Ozbek, Aydin, Kilic, Cenk, Kamburoglu, Kivanc, Ozen, Tuncer, Kavak, Vatan, Kirici, Yalcin, Oztas, Emin, Soysal, Handan Altinkaya, Unur, Erdogan, Ekinci, Nihat, Karaca, Omur, Malakhova, Olga, Kocaoglu, Murat, Toker, Serdar, Taser, Figen, Kilincoglu, Volkan, Yurtgun, Mustafa Fahri, Dalcik, Cannur, Zeybek, Ali, Baroncini, Marc, Peltier, Johann, Jissendi, Patrice, Pruvo, Jean-Pierre, Francke, Jean-Paul, Prevot, Vincent, Kosif, Rengin, Arifoglu, Yasin, Diramali, Murat, Sarsilmaz, Mustafa, Kose, Evren, Ogeturk, Murat, Akpinar, Burhan, Kus, Ilter, Meydan, Sedat, Kara, Alev, Kurtoglu, Zeliha, Tekdemir, Ibrahim, Elhan, Alaittin, Bas, Orhan, Odaci, Ersan, Mollaoglu, Hakan, Ucok, Kagan, Kaplan, Suleyman, Senoglu, Mehmet, Nacitarhan, Vedat, Kurutas, Ergul Belge, Senoglu, Nimet, Altun, Idris, Atli, Yalcin, Ozbag, Davut, Karakas, Sacide, Bilgin, M. Dincer, Tellioglu, Ayfer Metin, Ozlem, Sercin, Akcanal, Betul, Yildiz, Yuksel, Gunes, Hakki, Kose, Hayrullah, Uzum, Ibrahim, Gundogmus, Umit Naci, Caglayan, Cigdem, Pavlova, Velichka, Dimitrova, Mashenka, Georgieva, Lilia, Nikolova, Elena, Uzmansel, Deniz, Ozturk, Nail Can, Saylam, Canan Yurttas, Ozgiray, Erkin, Orhan, Mustafa, Cagli, Sedat, Zileli, Mehmet, Ozkan, Derya, Akkaya, Taylan, Comert, Ayhan, Balikci, Nilgun, Ozdemir, Esra, Gumus, Haluk, Ergul, Zafer, Kaya, Oskay, Altun, Serdar, Unlu, R. Erkin, Orbay, Hakan, Kim, Deog-Im, Han, Seung-Ho, Kim, Yi-Suk, Kim, Ho-Jeong, Lee, Kyu-Seok, Elcioglu, Omur, Ozden, Hilmi, Guven, Gul, Imre, Nurcan, Yalcin, Bulent, Ozan, Hasan, Akyer, Pinar, Guvencer, Mustafa, Karatosun, Vasfi, Sagoo, Mandeep Gill, Aland, Rachel Claire, Ustuner, Derya, Ustuner, M. Cengiz, Ai, Jafar, Ghazi, Seyed Reza, Mansouri, Seyed Hadi, Tuncer, Mehmet Cudi, Aluclu, Mehmet Ufuk, Karabulut, Ozlen, Hatipoglu, Eyup Savas, Nazaroglu, Hasan, Icke, Cigdem, Akbay, Emrah, Gunay, Turkan, Icke, Suleyman, Yildiz, Selda, Yazar, Fatih, Barlas, Barcin Orhan, Zahoi, Delia Elena, Kavakli, Ahmet, Tas, Ufuk, Dabak, Durrin Ozlem, Sapmaz, Hilal Irmak, Kocabiyik, Necdet, Ozer, Cenk Murat, Ozcan, Ayhan, Elevli, Levent, Desdicioglu, Kadir, Alanbay, Ibrahim, Govsa, Figen, Saylam, Canan Y., Akdogan, Ilgaz, Kiroglu, Yilmaz, Onur, Sule, Evcil, Emine Hilal, Cankara, Neslihan, Malas, Mehmet Ali, Kalcioglu, M. Tayyar, Duman, Serdar, Ulcay, Tufan, Uzun, Ahmet, Karabulut, Zulfu, Barut, Cagatay, Sevinc, Ozdemir, Yurdakan, Gamze, Kacar, Dundar, Erdogan, Ali Riza, Kurt, Hulyam, Demir, Bunyamin, Saltan, Mustafa, Burukoglu, Dilek, Ustuner, Mehmet Cengiz, Degirmenci, Irfan, Erdogan, Aliriza, Damar, Ozlem, Is, Merih, Bayramoglu, Gokhan, Kabay, Sahin, Uysal, Onur, Senturk, Hakan, Bayramoglu, Aysegul, Ozbayar, Cansu, Kutlu, Ali, Canbek, Mediha, Cevli, Salih Cenap, Hancerlioglu, Oguz, Koplay, Mustafa, Aksakalli, Elif, Dikici, Fatih, Kale, Aysin, Gayretli, Ozcan, Gurses, Ilke Ali, Ozdemir, Senem Turan, Ercan, Ilker, Baskan, Emel Bulbul, Yilmaz, Mediha, Ozkaya, Guven, Saricaoglu, Hayriye, Erturk, Mete, Kayalioglu, Gulgun, Uzel, Mehmet, Kahraman, Guler, Tanyeli, Ercan, Soyluoglu, Ali Ihsan, Tacar, Orhan, Demirant, Ayda, Bilgin, Murat, Karadede, Aziz, Aktas, Ayfer, Evcil, E. Hilal, Koyuncu, Esra, Sulak, Osman, Albay, Soner, Ozguner, Gulnur, Ozbek, Ahmet, Ozbek, Elvan, Ozturk, A. Hakan, Demirci, Tuba, Ciftcioglu, Engin, Demir, Mehmet Tevfik, Kopuz, Cem, Eroglu, Esra, Gedikli, Semin, Ozyurek, Hamit, Nural, Mehmet Selim, Incesu, Lutfi, Ogur, Gonul, Kara, Engin, Celebi, Baris, Yildiz, Altan, Altunkaynak, B. Zuhal, Kuvat, Samet Vasfi, Tagil, Suleyman Murat, Ertekin, Cumhur, Uysal, Hilmi, Bademkiran, Fikret, Albayrak, Nural, Esmer, Ali Firat, Coskun, Nigar Keles, Sindel, Muzaffer, Kizilay, Ferah, Yalin, Sevket, Karapinar, Nevin, Tokdemir, Mehmet, Karakurt, Lokman, Tumkaya, Levent, Korkmaz, Adnan, Ayas, Bulent, Ciftci, Nusret, Terzi, Yuksel, Baran, Ozlem, Nergiz, Yusuf, Akkus, Murat, Aluclu, Ufuk, Topal, Askin Ender, Yuksel, Dilek, Acar, Halil Ibrahim, Kendir, Simel, Hekimoglu, Emre, Basman, Deniz, Duman, Sunay, Ozener, Baris, Pelin, Can, Zagyapan, Ragiba, Kurkcuoglu, Ayla, Koc, Mustafa, Erdinc, Meral, Erdinc, Levent, Kelle, Ilker, Sancakdar, Enver, Cetin, Nil, Tunik, Selcuk, Yildirim, Ayse, Kaplanoglu, Iskender, Ayaz, Ercan, Ilhan, Necip, Okumus, Mehmet, Yuksel, Kasim Zafer, Ciralik, Harun, Yilmaz, Zeki, Gumusalan, Yakup, Gamsizkan, Mehmet, Kazkayasi, Mustafa, Dogan, Nadire Unver, Uysal, Ismihan Ilknur, Karalezli, Aylin, Fazliogullari, Zeliha, Buyukmumcu, Mustafa, Bozkurt, Mehmet Cem, Cicekcibasi, Aynur Emine, Demiryurek, Deniz, Ozsoy, M. Hakan, Bayramoglu, Alp, Tuccar, Eray, Baran, Ozlem Pamukcu, Soker, Sevda, Bahceci, Selen, Nasir, Yasemin, Yilmaz, Mehmet Tugrul, Cicekcibasi, Emine Aynur, Ulusoy, Mahinur, Gunaslan, Pervin, Bilge, Nuray, Akkaya, Muzaffer, Genc, Abdurrahman, Akcer, Sezer, Gonul, Yucel, Cosar, Emine, Koken, Gulengul, Ari, Ilknur, Bakirci, Sinan, Kafa, Ilker Mustafa, Uysal, Murat, Karabulut, Ahmet Kagan, Keles, Bahar, Emlik, Dilek, Uyar, Yavuz, Ozturk, Kayhan, Yilmaz, Neslihan Altuntas, Salbacak, Ahmet, Kacira, Burkay Kutluhan, Arazi, Mehmet, Demirci, Serafettin, Kiresi, Demet, Gumus, Serter, Seker, Muzaffer, Uyar, Mehmet, Astaneh, Mohammad Ebrahim, Khorshid, Alireza, Uygur, Ramazan, Songur, Ahmet, Sonmez, Osman Fikret, Dogan, Kamil Hakan, Kolcu, Giray, Iliescu, Madalina, Bordei, Petru, Iliescu, Dan, Ciobotaru, Camelia, Lucescu, Viorel, Covaleov, Anatoli, Ionescu, Constantin, Guirao, Miguel, Páramo, E., Mutuberria, R., Sánchez-Montesinos, I., Roda, O., Girón, F., Lopez-Soler, Miguel, Roda, Olga, Campos-López, Raúl, Guirao-Piñeiro, Miguel, Pascual-Morenilla, Maria Teresa, Sanchez-Montesinos, Indalecio, Pascual, Maria Teresa, Garzon, I., Serrato, D., Nieto-Aguilar, R., Sanchez-Montesinos, I., Sanchez-Quevedo, M., Ozdemir, M. Bulent, Ozean, R. Hakan, Bagdatli, Dilek, Adiguzel, Esat, Dogan, Zumrut, Aycan, Ozlem, Vardi, Nigar, Erkal, Haldun Sukru, Ozturk, Hakan, Mocanu, S., Stefanescu, C., Ionescu, A., Talpes, Raluca, Sapte, Elena, Dina, Constantin, Surdu, Loredana, Bulbuc, Ionut, Medina, M. T., Medina, J., López-Soler, M., Martin-Oviedo, Carlos, Lowy-Benoliel, Alejandro, Maranillo, Eva, Martinez-Guirado, Tomas, Sañudo, Jose, Scola, Bartolome, Vazquez, Teresa, Arráez-Aybar, L. A., Conejo-Menor, J. L., Gonzáles-Gómez, C. C., Torres-García, A. J., Nasu, Hisayo, Chiba, Shoji, Gutierrez-Semillera, M., Paksoy, Yahya, Kalaycioglu, Ahmet, Yildirim, Mehmet, Ozyasar, Ali, Ozdogmus, Omer, Cakmak, Yusuf Ozgur, Verimli, Ural, Cavdar, Safiye, Yildizhan, Begum, Aktan Ikiz, Z. Asli, Ucerler, Hulya, Ozgur, Zuhal, Yilmaz, Seher, Demirtas, Abdullah, Mavili, Ertugrul, Hacialiogullari, Mehtap, Susar, Hatice, Arslan, Seda, Aycan, Kenan, Ozkaya, Vecihi, Pilmane, Mara, Boka, Sarmite, Ortug, Gursel, Ramirez, Carlos, Pascual-Font, Aran, Valderrama-Canales, Francisco, Kucukalic, Abdulah, Kapur, Eldan, Talovic, Elvira, Baca, Vaclav, Grill, Robert, Horak, Zdenek, Kachlik, David, Dzupa, Valer, Konarik, Marek, Knize, Jakub, Veleminsky, Petr, Smrzova, Tereza, Otcenasek, Michal, Chmelova, Jana, Kheck, Michal, Kheck, Sr., Michal, Cupka, Tomas, Hnatek, Lukas, van der Meijs, Floris, Cech, Pavel, Musil, Vladimir, Ozkan, H. Mustafa, Muratli, S. Kivanc, Tayefi, Hamid, Ergur, Ipek, Kiray, Amac, Toktas, Muhsin, Alkoc, Ozan, Acar, Tolgahan, Uzun, Ibrahim, Ozen, Oguz Asian, Aycicek, Abdullah, Alkoc, Ozan Alper, Unlu, Mehmet, Corumlu, Ufuk, Ikiz, Ihsaniye Coskun, Oygucu, I. Hakan, Sendemir, Erdogan, Kaner, Tuncay, Caglar, Veli, Eser, Olcay, Demir, Mehmet T., Iyigun, Omer, Pirzirenli, Gokhan, Kaya, Ahmet Hilmi, Aydin, Mennan Ece, Celik, Fahrettin, True, Hakan, Ozkaya, Sevket, Ergur, Bekir Ugur, Zeybek, Gulsah, Bacakoglu, Kadir, Tadjalli, Mina, Poostpasand, Aghdas, Mansouiri, Seid Hadi, Allahvaisi, Ozra, Soleimanirad, Jafar, Nikkhoo, Bahram, Nagato, Yasukazu, Haruki, Yasuo, Yazawa, Komazo, Okazaki, Tutomu, Haida, Munetaka, Imai, Yutaka, Peirouvi, Thmineh, Mahzad-Sadaghiani, Mehrzad, Noroozinia, Farahnaz, Siamak, Salami, Farjah, Gholamhosseine, Mola, Sima, Biegaj, Ewa, Skadorwa, Tymon, Pawlewicz, Konrad, Kapolka, Robert, Chachulska, Agata, Zabicka, Joanna, Krasowska, Aleksandra, Prusik, Alicja, Jaczewski, Grzegorz, Kolesnik, Adam, Taghavi, M. Mohsen, Alavi, S. Hasan, Moallem, S. Adel, Safikhani, Zahed, Panahi, Marzieh, Dabiri, Shahriar, Shekaari, Majid Asadi, Latorre, Rafael, Soria, Federico, Lopez-Albors, Octavio, Sarria, Ricardo, Ayala, Inacio, Serrano, Inma, Perez-Cuadrado, Enrique, Musienko, Vladimir, Tkachenko, Dmitry, Colakoglu, Neriman, Kus, Murat Abdulgani, Jalali, Mahdi, Nikravesh, Mohammad Reza, Moeen, Abbas Ali, Karimfar, Mohammad Hassan, Rafighdoost, Houshang, Mohammadi, Shabnam, Korneeva, Marina, Rafighdoust, Houshang, Lovasova, Kvetuse, Bolekova, Adriana, Kluchova, Darina, Sulla, Igor, Kapitonova, Marina Yurievna, Syed Ahmad Fuad, Syed Baharom, Jayakaran, Flossie, Shams, Ali Reza, Aghaee, Fereshteh, Baqer, Zohreh, Faroki, Mohamad, Das, Srijit, Kassim, Normadiah, Latiff, Azian, Suhaimi, Frihah, Ghafar, Norzana, Hlaing, Khin Pa Pa, Maatoq, Israa, Othman, Faizah, Kiray, Muge, Bagriyanik, Husnu Alper, Pekcetin, Cetin, Ozogul, Candan, Fidan, Mustafa, Suhaimi, Farihah, Sun, Fei, Sanchez-Margallo, Francisco, Gil, Francisco, Crisostomo, Verónica, Uson, Jesus, Ramirez, Gegorio, Turamanlar, Ozan, Kirpiko, Oguz, Haktanir, Alpay, Climent, Salvador, Losilla, Sergio, Climent, Maria, Sarikcioglu, Levent, Senol, Yesim, Yildirim, Fatos B., Utuk, Arzu, Kunicki, Jacek, Pasbakhsh, Parichehr, Omidi, Negar, Omidi, Hamed, Nazhvani, Fatemeh Dehghani, Ghalebi, Seyed Razi, Javan, Nima, Mohagery, Akrami, Bideskan, Ali Reza Ebrahimzadeh, Taheri, Mohammad Mehdi Hassanzadeh, Fazel, Ali Reza, Tiengo, Cesare, Macchi, Veronica, Stecco, Carla, Porzionato, Andrea, Mazzoleni, Franco, De Caro, Raffaele, Clemente, Alberto, Morra, Aldo, Greco, Pietro, Pavan, Piero, Natali, Arturo, Demir, Mehmet, Dokur, Mehmet, Acer, Niyazi, Mavi, Ayfer, Matveeva, Niki, Lazarova, Dobrila, Korneti, Kostandina, Jovevska, Svetlana, Jurkovik, Dragica, Papazova, Meri, Havasi, Masoumeh, Alboghobeish, Naeim, Savari, Ahmad, Salamat, Negin, Sharifi, Mozafar, Kwak, Hyun-Ho, Hu, Kyung-Seok, Kim, Gyoo-Cheon, Park, Bong-Soo, Kim, Hee-Jin, Sinav, Ahmet, Gulati, Adarsh K., Gulati, Nidhi K., Alshammary, Hussien, Nazhvani, Seifollah Dehghani, Vafafar, Amir, Esmaeilpour, Tahereh, Bahmanpour, Soghra, Elyasi, Leila, Monabbati, Ahmad, Ghanadi, M., Paryani, Mohammad Reza, Gilanpour, Hassan, Amirsam, Banino, Omaña, Rodrigo Elizondo, López, Santos Guzmán, De la Garza Castro, Oscar, Vega, Edgar Urrutia, Lopez, Santos Guzman, Talebpour, Freshteh, Golmohammadi, Rahim, Dashti, Golamreza, Atlasi, Mohammad Ali, Mehdizadeh, Mehdi, Bahadori, Mohammad Hadi, Joghataei, Mohammad Taghi, Hatami, Leili, Boroujeni, Mandana Beigi, Estakhr, Jasem, Esfandiary, Ebrahim, Marzban, Mohsen, Bakhtiary, Mehrdad, Modiry, Navid, Jafarpur, Mokhtar, Mofidpur, Hassan, Alavi, S. Hassan, Mahmoudian, Alareza, Taghavi, Mohmmad Mohsen, Jafarpour, Mokhtar, Mahmoudian, Ali Reza, Sanjarmousavi, Nasrin, Doassans, Ines, Sorrenti, Natalia, Decuadro, German, Saibene, Andres, Poumayrac, Marie, Laza, Sebastian, Almiron, Carina, Vergara, Maria Elena, Soria, Victor, Lasa, Sebastian, Perez, Adolfo, Castro, Gabriela, Maria, Ana Santa, Soleimani, Mansoureh, Katebi, Majid, Bakhshayesh, Masoomeh, Oner, Mithat, Halici, Mehmet, Yikilmaz, Ali, Guney, Ahmet, Turk, Yildirim, Edizer, Mete, Beden, Umit, Icten, Nihal, Afshar, Mohammad, Hasanzadeh Taheri, Mohammad Mehdi, Moalem, Adel, Golalipour, Mohammad Jafar, Tamizi, Azadeh, Ahi, Mohammad, Mohammadpour, Shahram, Maiery, Ardeshir, Acikel, Cengiz, Ulkur, Ersin, Karagoz, Huseyin, Celikoz, Bahattin, Bedi, Kuldip, Ginus, Partadiredja, Golalipoor, Mohammad Jafar, Mohammadi, Mohammad Reza, Jhand, Poya, Mansourian, Azad Reza, Hosseinpoor, Kanizreza, Keshtkar, Abbas Ali, Alsaffar, Raith, Balajadeh, Babak Kabiri, Ghafari, Soraya, Azarhosh, Ramin, Fazeli, Seyyed Amirhossein, Jahanshahi, Mehrdad, Gharravi, Annen Mohammad, Alicioglu, Banu, Karakas, Hakki Muammer, Harma, Ahmet, Yang, Hun-Mu, Won, Sung-Yoon, Lee, Jae-Gi, Lee, Ju-Young, Lee, Jeong-Yong, Kim, Yoo-Ri, Song, Wu-Chul, Koh, Ki-Seok, Hwang, Eu-Na, Choi, Hyun-Gon, Kim, Soon-Heum, Kim, Soo-Young, Hur, Mi-Sun, Ulucam, Enis, Celbis, Osman, Kim, Da-Hye, Hong, Hee-Suk, Kim, Hyun-Joo, Choi, Jong-Hoon, Park, Jong-Tae, Kim, Hyeon-Cheol, Abbasi, Hamed, Hosseinipanah, Seyed Mohammad, Hosseini, Mohammad, Amani, A., Ashrafi, H. R., Sadeghimehr, Mohsen, Kim, Hyun-Ju, Sheverdin, Vadim, Amani, Zahra, Ashrafi, Alireza, Ashrafi, Ali Reza, Javad, Hami, Kachap, Mokhtar Jafarpoor, Laza, Sebastián, Poumayrac, Marie Catherine, Doassans, Inés, Vergara, María Elena, Almirón, Carina, Soria, Víctor, Rivara, Alvaro, Sirilo, Angela, Freire, Diego, Cirillo, Angela, Veragara, Maria Elena, Krmek, Vlado, Krmek, Nikola, Jo-Osvatic, Ana, Nikolic, Vasilije, Radic, Radivoje, Tubbs, R. Shane, Loukas, Marios, Fogg, Quentin, Ashwood, Neil, Cilingiroglu, Serpil, Ozbakir, Cemal, Mazoochi, Tahereh, Sabanciogullari, Vedat, Gumus, Cesur, Erdil, F. Hayat, Cimen, Mehmet, Moodi, Hesam, Ghiasi, Fateme, Akbari, Asghar, Hami, Javad, Khazei, Majid, Haghparast, Elham, Mitsakis, Ioannis, Anastasiou, Aikaterini, Mitsakis, Menelaos, Sianou, Kyriaki, Hainoglou, Roxani, Francisco, Margarida, Mitsaki, Charikleia, Konstantinidi, Maria, Prapa, Stamatia, Leksan, Igor, Mrcela, Tomislav, Selthofer, Robert, Kermanian, Fatemeh, Mahmoudian, Alireza, Ahmadpoor, Mahmood Erfanian, Dalili, Naser, Elian, Amir Hossein, Moaiery, Ardesheer, Jamalpour, Zahra, Nourani, Mohammad Reza, Asgari, Alireza, Hassanzadeh Taheri, Mohammad Mehdi, Ebrahimzadeh, Alireza, Eftekharvaghefi, Seyed Hasan, Mohammadi, Abbas, Sheibani, Vahid, Nematollahi-Mahani, Seyed Noureddin, Latifpour, Mastafa, Deilami, Masood, Soroure-Azimzadeh, Behzad, Nabipour, Fatemeh, Najafipour, Hamid, Nakhaee, Nouzar, Yaghoobi, Mohammad, Eftekharvaghefi, Rana, Salehinejad, Parvin, Azizi, Hasan, Riasi, Hamid Reza, Nobakht, Maliheh, Asalgoo, Sara, Rahbar, Roshanak, Najafzadeh, Norooz, Moosavizadeh, Kazem, Ezzatabadypour, Massood, Majidi, Masoud, Malekpor-Afshar, Reza, Karimzade, Fariba, Hoseini, Mahmood, Bayat, Mohamad, Gorgi, Ali, Nezhadi, Akram, Bakhtiari, Mehrdad, Jazi, Homa Rasooli, Jafaryan, Maryam, Haghir, Hosein, Hosseini, Mahmood, Rahimi, Sadegh, Rassouli, Fatemeh Behnam, Gorji, Ali, Habibi, Aliasghar, Pouya, Fatemeh, Dabiri, Shahryar, Mousavi, A., Rajabalian, Saeed, Abolidokht, A., Khanlarkhani, Neda, Naderian, Homayoun, Berjis, Nezamedin, Namavar, Mohamad Reza, Talaei, Tahereh, Mazaheri, Zohreh, Monabati, Ahmad, Kosar, Mehmet Ilkay, Karacan, Kezban, Chegini, Hamidreza, Nikzad, Hossein, Ayhan, Egemen, Ustundag, Sinan, Akkin, Salih Murat, Ogut, Tahir, Rayegan, Parviz, Meibodi, Mohamad Ali Emami, Ghaem, Reza Montazer, Zargarpoor, Rosa, Eftekhar Vaghefi, Seyd Hasan, Moshkdanian, Ghazale, Poya, Fateme, Kohestani, Hamid, Abarghoeai, Roozbeh Rayegan, Abarghoeai, Parviz Rayegan, Eftekhar Vaghefi, Seyed Hasan, Mahmodi, Abolghasem Amir, Poraboli, Ali, Kohestani, Hamid Reza, Vaghefi, Raena Eftekhar, Eftekhar Vaghefy, Seyed Hasan, Vaghefy, Raena Eftekhar, Abarghoeai, Parviz Raygan, Saba, Mohamad, Gharravi, Anneh Mohammad, Javadnia, Fatemeh, Zhaleh, Mohsen, Nezhad, Dariush Bijan, Gholami, Mohammad Reza, Piagkou, Maria, Aikaterini, Vassiliki Kouki, Piagkos, Giannoulis, Douvetzemis, Stergios, Skandalakis, Panagiotis, Anagnostopoulou, Sophia, Papadopoulos, Nikolaos, Celik, H. Hamdi, Tatar, Ilkan, Tatar, Emel Cadalli, Mocan, Burce Ozgen, Sargon, Mustafa F., Denk, C. Cem, Rasoolijazi, Homa, Joghataie, Mohammad Taghi, Roghani, Mehrdad, Akkin, Salin Murat, Dinc, Gulten, Kurklu, Mustafa, Ozboluk, Sener, Komurcu, Mahmut, Koebke, Jürgen, Balioglu, Mehmet Bulent, Kaygusuz, Mehmet Akif, Bozkus, Ferdi Sefa, Korkmaz, Ozgur, Bayram, Sule Biyik, Can, Mehmet Ali, Nasiri, Ebrahim, Jafar-Kazemi, Koroush, Hosseini, Melina, Maghoul, Shahin, Soleimani, Mansooreh, Amini, Abdollah, Hassanzade, Mohamad Mahdi, Davari, Mohammad Hossein, Van Hoof, Tom, Gomes, Germano T., Audenaert, Emmanuel, Verstraete, Koenraad, Kerckaert, Ingrid, D’Herde, Katharina, Benninger, Brion, Hedley, Gil, Filipoiu, Florin Mihail, Tarta, Eugen, Enyedi, Mihali, Pantu, Cosmin, Stanciulescu, Razvan, Skobowiat, Cezary, Calka, Jaroslaw, Majewski, Mariusz, Rezaian, Maryam, Yaghoobfar, Akbar, Hamedi, Somayeh, and Shomali, T.

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2009
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