Dr. Oezdemir Cetin
Postdoctoral Researcher
Contact
oezdemir.cetin@tu-...
work +49 6151 16-57 366
Work
S3/06 201
Merckstrasse 25
64283
Darmstadt
Oezdemir Cetin joined the SOS Lab as a visiting professor in February 2018. Subsequently, his project entitled “Rapid segmentation and tracking of yeast cells in microfluidic structures using convolutional neural networks for the measurement of cell fluorescence,” submitted to the AvH Philipp Schwartz Initiative, was accepted in 2020. Extending his project work by shifting it to histopathology images, he continues to work with Frankfurt University Hospital. The updated study mainly concerns the follow-up and counting of cancer cells in histopathology images. Various machine learning techniques are used for this.
His research interests include computational pathology and topics such as bayesian inference, vision transformation, graph networks, multiple-instance learning, and uncertainty in deep learning.
Passionate students who want to work in the computational pathology field can contact me for more information about the topics listed below.
Publications (selected)
| 2023 |
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| Cetin, O., Lai, J., Ziegler, P., Wild, P., Dogali, G. & Koeppl, H. (2023, December). Keypoint-Driven Unsupervised Learning for Histopathology Image Registration. In 2023 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (pp. 3514-3520). IEEE. |
| 2022 |
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| Gul, A. G., Cetin, O., Reich, C., Flinner, N., Prangemeier, T., & Koeppl, H. (2022, April). Histopathological image classification based on self-supervised vision transformer and weak labels. In Medical Imaging 2022: Digital and Computational Pathology(Vol. 12039, pp. 366-373). SPIE. |
| Cetin, O., Shu, Y., Flinner, N., Ziegler, P., Wild, P., & Koeppl, H. (2022, February). Multi-magnification networks for deformable image registration on histopathology images. In 10th International Workshop on Biomedical Image Registration. |
| Cetin, O., Chen, M., Ziegler, P., Wild, P., & Koeppl, H. (2022, December). Deep learning-based restaining of histopathological images. In 2022 IEEE International Conference on Bioinformatics and Biomedicine (BIBM) (pp. 1467-1474). IEEE. |
| 2021 |
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| Reich, C., Prangemeier, T., Cetin, Ö., & Koeppl, H. (2021). OSS-Net: Memory Efficient High Resolution Semantic Segmentation of 3D Medical Data. arXiv preprint arXiv:2110.10640. |
| 2020 |
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| Cetin, O., Seymen, V., & Sakoglu, U. (2020). Multiple sclerosis lesion detection in multimodal MRI using simple clustering-based segmentation and classification. Informatics in Medicine Unlocked, 20, 100409. |
Student Projects (on going)
| Master Thesis | ||
|---|---|---|
| Wenxin Zhao | Multiobject Optimization | since 15.10.2023 |
| Can Pehlivan | Advancing Cell Segmentation: Comparative Analysis of Attention-Based and Visual Transformers | since 15.09.2023 |
Student Projects (completed)
| Master Thesis | ||
|---|---|---|
| Ailian Tian | Determining the Capabilities and Limitations of Latent Diffusion Models for Whole Slide Image Synthesis: A Case Study | 31.10.2023 |
| Jennifer Leichtle | A Comparative Analysis of Cell Segmentation Techniques for Histopathological Images | 25.07.2023 |
| Junming Lai | Enhancing Non-Rigid Medical Image Registration Performance through Keypoint-Based Frameworks | 20.07.2023 |
| Xin Li | Representing Uncertainty in Weakly Supervised Deep Learning for Histopathology Image Segmentation | 23.03.2023 |
| Nan Yin | A vision transformer-based Graph neural network for Immune cell segmentation | 16.03.2023 |
| Yankun Wu | Virtual stain transformation of histopathological images based on deep-learning | 21.09.2022 |
| Mingzhi Chen | Contrastive learning-based stain transformation for cancer grading | 03.03.2022 |
| Yahia Brini | Image-based molecular subtyping of cancer through deep learning | 20.01.2022 |
| Yiran Shu | Deep neural network based non-rigid image registration for histopathological images | 14.01.2022 |
| Ahmet Gökberk Gül | Histopathological Image Classification Based on Self-Supervised Vision Transformer | 25.11.2021 |
| Rijan Kusatha | Multiple instance learning for cancer molecular subtype classification | 03.09.2021 |
| Jiajun Deng | Image registration for multi-stained histopathologicalwhole slide images | 27.08.2021 |
| Berkay Canel | Segmentation of Multiple Sclerosis Lesions on Magnetic Resonance Data of the Human Brain with Convolutional Neural Networks | 18.12.2020 |
Student Projects (available)
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