RESEARCH AREA:

Computational Neuroanatomy & Fetal Imaging (UNIL-CHUV)

Section Head: Dr. Meritxell Bach Cuadra, MER, PD (UNIL)

The CHUV-UNIL SP Section includes 8 engineers with the aim at developing novel image processing methods to allow a more effective use of emerging medical images, balanced between fundamental research aspects of image processing, machine learning and application-oriented projects. Our research is applied in several clinical domains like computer aided diagnostic and therapy planning procedures. Our aim is to facilitate true clinical adoption of the developed methods and tools by strongly engaging interdisciplinary joint effort of engineers and clinicians. To do so, we benefit from a unique research environment, with access to several state-of-the-art clinical MRI scanners, and we have active collaborations with the CHUV departments of Radiology, Neurology, Neuro-surgery, Oncology, Psychiatry and Cardiology as well as with many regional and international collaborators in academia and industry.

RESEARCH TOPICS

Super-Resolution T2w Foetal Brain MRI for Computer Assisted Diagnosis and Quantitative Analysis

Description: We develop advanced quantitative imaging techniques for studying the maturation of the in-vivo human brain in its early stages of development, when it undergoes the most significant changes. One research line is dedicated to the image super-resolution reconstruction and segmentation of T2w fetal imaging. This will provide accurate quantitative analysis of the growing brain anatomy by morphological biomarkers. Another research line is related to support the translation of the developed reconstruction and segmentation methods to the clinical environment and their evaluation in daily exploration of fetal brain MR images. This research is supported by Swiss National Science Foundation (205321_182602 and 205321_141283), Haslerstiftung and the Radiology Department of the Lausanne University Hospital.

Investigators: Priscille de Dumast (UNIL), Hamza Kebiri (UNIL), Hélène Lajous (UNIL), Meritxell Bach Cuadra (UNIL)

Collaborators: Dr. S. Tourbier (Radiology Department CHUV), Prof. P. Hagmann (Radiology Department CHUV), Prof. P. Maeder (Radiology Department CHUV), Dr V. Dunet (Radiology Department CHUV), Dr. M. Koob (Radiology Department CHUV), Prof. R. Meuli (Radiology Department CHUV), T. Yu (EPFL), Prof. J.-Ph. Thiran (EPFL), Dr. B. Marechal (Siemens Healthcare), M. R. Corredor (Siemens Healthcare)

Super-resolution reconstruction of in-vivo diffusion brain MRI

Description: The assessment of in-vivo fetal brain maturation is not only linked to morphology but also to physiological processes, thus the underlying microstructural changes need also to be imaged. Diffusion MRI (dMRI) allows to depict the underlying tissue microstructure but it suffers from a coarse spatial-resolution. A major research topic is to develop a super-resolution framework encompassing image artefact correction, motion estimation and dMRI reconstruction.  Our work will include spherical harmonics (SH) representation of the signal with spatial-angular regularization and single-volume SR strategies with machine learning-based algorithms. This research is supported by Swiss National Science Foundation (205321_182602 and 205321_141283).

Investigators: Hamza Kebiri (UNIL), Priscille de Dumast (UNIL), Hélène Lajous (UNIL), Meritxell Bach Cuadra (UNIL)

Collaborators: Dr. Y. Alemán-Gómez (Radiology Department CHUV), Dr. S. Tourbier (Radiology Department CHUV), Prof. P. Hagmann (Radiology Department CHUV), Prof. P. Maeder (Radiology Department CHUV), Dr V. Dunet (Radiology Department CHUV), Dr. M. Koob (Radiology Department CHUV), Prof. R. Meuli (Radiology Department CHUV), T. Yu (EPFL), Prof. J.Ph. Thiran (EPFL), Dr. A. Jakab (Kinderspital Zürich)

Quantitative MR Imaging (qMRI) of the in vivo fetal brain

Description: In combination with the planned advancement of foetal T2w and dMR imaging described above, we aim at developing new qMRI sequences for T1 and T2 mapping of the foetal brain. QMRI has proven its ability not only to depict brain maturation but also abnormal patterns and developmental schemes in preterm and new-born babies. The possibility to image these quantitative characteristics in utero would be a major breakthrough in foetal MRI. In this research project, we will combine our SR framework with fast qMRI acquisition schemes tailored to deal with foetal motion. This research is supported by Swiss National Science Foundation (205321_182602 and 205321_141283).

Investigators: Hélène Lajous (UNIL), Hamza Kebiri (UNIL), Priscille de Dumast (UNIL), Hélène Lajous (UNIL), Jean Batiste Ledoux (CHUV), Christopher W. Roy (CHUV), Matthias Stuber (CHUV), Ruud Van Heeswijk (CHUV), Meritxell Bach Cuadra (UNIL)

Collaborators: Dr. S. Tourbier (Radiology Department CHUV), Prof. P. Hagmann (Radiology Department CHUV), Prof. R. Meuli (Radiology Department CHUV), T. Yu (EPFL), Prof. J.-Ph. Thiran (EPFL), Dr. T. Hilbert (Siemens Healthcare), Dr. D. Piccini (Siemens Healthcare), Dr. T. Kober (Siemens Healthcare)

Machine learning methods for MRI analysis in Multiple Sclerosis

Description: We have developed jointly with our collaborators many machine learning methods for the detection and segmentation of white matter and cortical lesions based on MRI of Multiple Sclerosis. Our major contribution has been the development of a partial-volume method to detect small lesions, even in the earliest stages of the disease. Our methods have been developed for clinical MRI setting and also for more advanced MRI sequences at 3T and 7T. Furthermore, we also investigate support diagnosis and prognostic tools based on advanced MRI-based biomarkers (central vein sign and rim sign). This project is supported by European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie project TRABIT (agreement No 765148).

Investigators:  Francesco La Rosa (EPFL), Hamza Kebiri (UNIL), Meritxell Bach Cuadra (UNIL)

Collaborators: Prof. C. Granziera (University Hospital Basel and University of Basel), Dr. M.J. Fartaria (Siemens Healthcare), Dr J. Richiardi (Siemens Healthcare), Dr. T. Kober (Siemens Healthcare), Dr. P. Maggi (CHUV), Prof. Du Pasquier (CHUV), Prof. R. Meuli (CHUV), Dr. A. Abdulkadir (University of Pennsylvania), Dr. M. Absinta (Johns Hopkins University), Dr E. Beck (Translational Neuroradiology Section – NIH), Dr. P. Sati (Translational Neuroradiology Section – NIH), Dr. D. Reich (Translational Neuroradiology Section – NIH)