Breast MRI
Breast MRI is the most sensitive technique for breast cancer detection available. For screening, the method is at this moment still reserved for patients at high risk for the development of breast cancer, but the indications are widening. In virtually every population of breast MRI compared to mammography, the breast cancer detection rate nearly doubles.
There is, therefore, a clear incentive to offer breast MRI as a screening technique to many more women than is currently done. However, this is limited by the lack of good scanners and the relatively high cost of this examination. We develop algorithms to assist in the interpretation of breast MRI and investigate techniques to create shorter breast MRI protocols by adapting the protocol dynamically during the MRI acquisition. This requires us to develop real-time reconstruction and detection algorithms. As such, our research on breast MRI is also neatly integrated with our research on reconstruction.
Publications
- M. U. Dalmiş, A. Gubern-Mérida, S. Vreemann, P. Bult, N. Karssemeijer, R. Mann, J. Teuwen, "Artificial Intelligence–Based Classification of Breast Lesions Imaged With a Multiparametric Breast MRI Protocol With Ultrafast DCE-MRI, T2, and DWI", Investigative Radiology, 2019, 54;(6):325-332
- F. Ayatollahi, S. B. Shokouhi, J. Teuwen, "Differentiating benign and malignant mass and non-mass lesions in breast DCE-MRI using normalized frequency-based features", International Journal of Computer Assisted Radiology and Surgery, 2019, 15;(2):297-307
- F. Ayatollahi, S. B. Shokouhi, R. M. Mann, J. Teuwen, "Automatic Breast Lesion Detection in Ultrafast DCE-MRI Using Deep Learning", 2021
- R. Samperna, N. Moriakov, N. Karssemeijer, J. Teuwen, R. M. Mann, "Exploiting the Dixon Method for a Robust Breast and Fibro-Glandular Tissue Segmentation in Breast MRI", Diagnostics, 2022, 12;(7):1690
- L. Han, T. Tan, T. Zhang, Y. Huang, X. Wang, Y. Gao, J. Teuwen, R. Mann, "Synthesis-based Imaging-Differentiation Representation Learning for Multi-Sequence 3D/4D MRI", 2023
- T. Zhang, T. Tan, L. Han, X. Wang, Y. Gao, J. Teuwen, R. Beets-Tan, R. Mann, "IMPORTANT-Net: Integrated MRI Multi-Parameter Reinforcement Fusion Generator with Attention Network for Synthesizing Absent Data", 2023
