skip to content

Center for Data and Simulation Science

Dr. Liliana Caldeira is a team leader at the University Hospital of Cologne, where she leads her team in innovative data science research in the field of radiology. The team focuses on the development and implementation of AI algorithms using 3D medical images such as Computed Tomography (CT) and Magnetic Resonance Imaging (MRI). The team is part of the radiology department, supporting the creation of high quality datasets and the evaluation of AI algorithms.

expand:
Source 3D MRI image (FLAIR contrast – most left) and three synthetically generated 3D MRI images of different contrasts (from left to right: T1-weighted, T2-weighted and T1-weighted with contrast agent) and respective Deep Learning segmentations of brain tumour regions (green –edema, blue – necrotic core, red – contrast-enhanced tumour).

Selected publications

  1. L. Pennig, C. Hoyer, L. Goertz, R. Shahzad, T. Persigehl, M. Perkuhn, M. Ruge, C. Kabbasch, J. Borggrefe, L. Caldeira*, K. R. Laukamp*. Primary Central Nervous System Lymphoma: Clinical Evaluation of Automated Segmentation on Multiparametric MRI Using Deep Learning. Journal of Magnetic Resonance Imaging. 2020. *indicates shared last co-authorship.
  2. S. Lennartz, A. Mager, N. Große Hokamp, S. Schäfer, D. Zopfs, H.C. Reinhardt, R.K. Thomas, L. Caldeira*, T. Persigehl*. Texture analysis of iodine maps and conventional images for K-nearest neighbor classification of benign and metastatic lung nodules. Cancer Imaging 2021. *indicates shared last co-authourship
  3. Terzis, R., Reimer, R.P., Nelles, C., Celik, E., Caldeira, L., Heidenreich, A., Storz, E., Maintz, D., Zopfs, D. and Große Hokamp, N., 2023. Deep-Learning-Based Image Denoising in Imaging of Urolithiasis: Assessment of Image Quality and Comparison to State-of-the-Art Iterative Reconstructions. Diagnostics, 13(17), p.2821.
  4. Rinneburger, M., Carolus, H., Iuga, A.I., Weisthoff, M., Lennartz, S., Hokamp, N.G., Caldeira, L., Shahzad, R., Maintz, D., Laqua, F.C. and Baeßler, B., 2023. Automated localization and segmentation of cervical lymph nodes on contrast-enhanced CT using a 3D foveal fully convolutional neural network. European Radiology Experimental, 7(1), p.45.
  5. P. Woznicki, F. Siedek, Maatje D A van Gastel, D. Pinto Dos Santos, S. Arjune, L.A Karner, F. Meyer, L.L. Caldeira, T. Persigehl, R.T. Gansevoort, F. Grundmann, B. Baessler, R.U. Müller Automated Kidney and Liver Segmentation in MR Images in Patients with Autosomal Dominant Polycystic Kidney Disease: A Multicenter Study. Kidney 360 2022.
  6. P.A. Wawer Matos, R.P. Reimer, A.C. Rokohl, L. Caldeira, L. M. Heindl, N. Große-Hokamp. Artificial Intelligence in Ophthalmology – status quo and future. Seminar In Ophthalmology 2022.
  7. R.J. Gertz, F. Gerhardt, J.R. Kröger, R. Shahzad, L. Caldeira, J. Kottlors, N. Große Hokamp, D. Maintz, S. Rosenkranz, A.C. Bunck. Spectral Detector CT-Derived Pulmonary Perfusion Maps and Pulmonary Parenchyma Characteristics for the Semiautomated Classification of Pulmonary Hypertension. Frontiers in Cardiovascular Medicine 2022.  
  8. A.I. Iuga, T. Lossau, L. Caldeira, M. Rinneburger, S. Lennartz, N. Große Hokamp, M. Püsken, H. Carolus, D. Maintz, T. Klinder, T. Persigehl Automated mapping and N-Staging of thoracic lymph nodes in contrast-enhanced CT scans of the chest using a fully convolutional neural network. European Journal of Radiology 2021.
  9. L. Pennig, R. Shahzad, L. Caldeira, S. Lennartz, F. Thiele, L. Goertz, D. Zopfs, A.-K. Meißner, G. Fürtjes, M. Perkuhn, C. Kabbasch, S. Grau,  J. Borggrefe, K.R. Laukamp. Automated detection and segmentation of brain metastases in malignant melanoma: Clinical evaluation of a dedicated deep learning model. American Journal of Neuroradiology 2021.
  10. T. Dratsch, L. Caldeira, D. Maintz, D.P. dos Santos. Artificial intelligence abstracts from the European Congress of Radiology: analysis of topics and compliance with the STARD for abstracts checklist. Insights into Imaging. 2020.