Coordinator: Prof. Dr. Devrim Ünay
AIDA Vision Lab aims to bring algorithmic solutions to real-life computer vision related problems.
Our main research topics are
- Computer vision and pattern recognition
- Biomedical image processing
- Machine / deep learning
- Information retrieval
- Data mining.
Selected projects of our lab:
- Development of Image Processing and Machine Learning based Tools for Analysis of Phase-Contrast Optical Microscopy Time Series Images. TÜBİTAK ARDEB 1001. 2020-2023
- A new Network of European BioImage Analysts to advance life science imaging (NEUBIAS). EU Cost Action CA15124. 2016-2020
- Probabilistic and Machine Learning-based Methods for Automatic Dendritic Spine Segmentation, Classification, and Tracking in Two-Photon Microscopy Images. TÜBİTAK ARDEB 1001. 2014-2017
- Comparing Visual and computer-based ratings of dementia-related neuroimaging findings. TÜBİTAK ARDEB 3501 Career Grant. 2011-2014
Selected publications of our lab:
- Erdem, Y. S., Iheme, L. O., Uçar, M., Özuysal, Ö. Y., Balıkçı, M., Morani, K., Töreyin, B. U., Ünay, D. Novel Neural Style Transfer based data synthesis method for phase-contrast wound healing assay images. Biomedical Signal Processing and Control, 96, 106514, 2024.
- Morani, K., Ayana, E. K., Kollias, D., & Unay, D. COVID‐19 Detection from Computed Tomography Images Using Slice Processing Techniques and a Modified Xception Classifier. International Journal of Biomedical Imaging, 2024(1), 9962839.
- Ucar, M., Iheme, L. O., Onal, S., Pesen-Okvur, D., Yalcin-Ozuysal, O., Toreyin, B. U., & Unay, D. Blank Frame and Intensity Variation Distortion Detection and Restoration Pipeline for Phase-Contrast Microscopy Time-Lapse Images. Electrica, 24(1), 2024.
- Yao, J., Xing, J., Zheng, F., Li, Z., Li, S., Xu, X., Unay, D., Song, Y.M., Yang, F., Wu, A., Dual-infinite coordination polymer-engineered nanomedicines for dual-ion interference-mediated oxidative stress-dependent tumor suppression, Materials Horizons, 2023.
- Argunşah, A. Ö., Erdil, E., Ghani, M. U., Cortés, Y. R., Hobbiss, A. F., Karayannis, T., Çetin, M., Israely, I., Ünay, D., An interactive time-series analysis software for dendritic spines, Scientific Reports, 12,12405, 2022.
- Unay, D., Deep Learning based Automatic Grading of Bi-Colored Apples using Multispectral Images, Multimedia Tools and Applications, 81, 38237–38252, 2022.
- Soyak, R., Navruz, E., Ersoy, E.O., Cruz, G., Prieto, C., King, A.P., Unay, D., Oksuz, I., Channel Attention Networks for Robust MR Fingerprint Matching, IEEE Transactions on Biomedical Imaging, 69(4), 1398-1405, 2022.
- M. Lucidi; D.E. Tranca; L. Nichele; D. Unay; G.A. Stanciu; P. Visca; A.M. Holban; R. Hristu; G. Cincotti; S.G. Stanciu, SSNOMBACTER: A collection of scattering-type Scanning Near-Field Optical Microscopy and Atomic Force Microscopy images of bacterial cells, GigaScience, 9(11), 1-12, 2020.
- Rubens, U., Mormont, R., Baecker, V., Michiels, G., Paavolainen, L., Ball, G., Unay, D., Pavie, B., Chessel, A., Scholz, L., Maska, M., Hoyoux, R., Vandaele, R., Stanciu, S., Golani, O., Sladoje, N., Paul, P., Marée, R., Tosi, S., BIAFLOWS: A collaborative framework to benchmark bioimage analysis workflows, 10.1101/707489, 2020, Patterns – Cell Press (accepted). You can also check the interview in Prelights.
- Yalciner, B.Z., Kandemir, M., Taskale, S., Tepe, S.M., Unay, D., “Modified Visual MR Rating Scale for Evaluation of Patients with Forgetfulness” Canadian Journal of Neurological Sciences, 46 (1), 71-78, 2019.
- Rada, L., Kilic, B., Erdil, E., Ramiro-Cortez, Y., Israely, I., Unay, D., Cetin, M., Argunsah, A.O., “Tracking-assisted Detection of Dendritic Spines in Time Lapse Microscopic Images” Neuroscience, 394, 198-205, 2018.
- Unay, D., Stanciu, G.S., “An evaluation on the robustness of five popular keypoint descriptors to image modifications specific to laser scanning microscopy” IEEE Access, 6, 40154-40164, 2018.
- Müller, H., Unay, D., “Retrieval from and Understanding of Large-Scale Multi-Modal Medical Datasets: A Review”, IEEE Transactions on Multimedia, 19(9), 2093-2104, 2017.
- Erdil, E., Ghani, M.U., Rada, L., Argunsah, A.O., Unay, D., Tasdizen, T., Cetin, M., “Nonparametric Joint Shape and Feature Priors for Image Segmentation”, IEEE Transactions on Image Processing, 26(11), 5312-5323, 2017.
- Carass, A., et al., “Longitudinal Multiple Sclerosis Lesion Segmentation: Resource and Challenge” NeuroImage, 148, 77-102, 2017.
- Ghani, M.U., Mesadi, F., Kanik, S.D., Argunsah, A.O., Hobbiss, A.F., Israely, I., Unay, D., Tasdizen, T., Cetin, M., “Dendritic Spine Classification using Shape and Appearance Features based on Two-Photon Microscopy”, Journal of Neuroscience Methods, 279, 13-21, 2017.