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Maryam Sadeghi, PhD student
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Main research topics
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Artificial Intelligence, Medical Image processing, Digital pathology
Recent Projects
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Image Analysis of histological flouroscent Mouse Brain sections:
- Image Classification
- Image Registration
- Image Preprocessing & Analysis
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histological H&E stained Renal Whole Slide Images:
- Image Classification
- Image Segmentation
- Explainability in AI (XAI)
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Breast Cancer Lymph Node Metastasis Detection in H&E stained histological images using Convolutional Neural Networks
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Detection of small tumors in IR thermographic breast imaging
Publications
- Sadeghi, M., Neto, P., Ramos-Prats, A., Castaldi, F., Paradiso, E., Mahmoodian, N., ... & Goebel, G. (2022, April). Automatic 2D to 3D localization of histological mouse brain sections in the reference atlas using deep learning. In Medical Imaging 2022: Image Processing (Vol. 12032, pp. 718-724). SPIE.
- Sadeghi, M., Maldonado, I., Abele, N., Haybaeck, J., Boese, A., Poudel, P., & Friebe, M. (2019, July). Feedback-based self-improving CNN algorithm for breast cancer lymph node metastasis detection in real clinical environment. In 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 7212-7215). IEEE.
- Sadeghi, M., Boese, A., Maldonado, I., Friebe, M., Sauerhering, J., Schlosser, S., ... & Wehberg, K. (2019). Feasibility test of dynamic cooling for detection of small tumors in IR thermographic breast imaging. Current Directions in Biomedical Engineering, 5(1), 397-399.
- Sanaat, A., Shooli, H., Böhringer, A. S., Sadeghi, M., Shiri, I., Salimi, Y., ... & Zaidi, H. (2023). A cycle-consistent adversarial network for brain PET partial volume correction without prior anatomical information. European Journal of Nuclear Medicine and Molecular Imaging, 1-16.
- Ramos-Prats, A., Paradiso, E., Castaldi, F., Sadeghi, M., Mir, M. Y., Hörtnagl, H., ... & Ferraguti, F. (2022). VIP-expressing interneurons in the anterior insular cortex contribute to sensory processing to regulate adaptive behavior. Cell Reports, 39(9), 110893.
- Mahmoodian, N., Thadesar, M. H., Sadeghi, M. M., Georgiades, M., Pech, M., & Hoeschen, C. (2022). LIVER TUMOR SEGMENTATION USING DEEP LEARNING METHOD: RESLU-NET. Physica Medica: European Journal of Medical Physics, 104, S132.
- Mahmoodian, N., Thadesar, H., Sadeghi, M., Georgiades, M., Pech, M., & Hoeschen, C. (2022). Segmentation of Living and ablated Tumor parts in CT images Using ResLU-Net. Current Directions in Biomedical Engineering, 8(2), 49-52.
- Poudel, P., Illanes, A., Sadeghi, M., & Friebe, M. (2019, July). Patch based texture classification of thyroid ultrasound images using convolutional neural network. In 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 5828-5831). IEEE.
Teaching
- See here