• Third PhD in biomedical Engineering – Edgard Nyssen.
• After the creation of IMEC, the semiconductor technology is extended with LPCVD, e-beam processing, sputtering, plasma deposition, etching, lithography mask alignment up to 0.25 µm and measurement equipment. Technical personnel are recruited. The semiconductor technology team counts 5 members.

HealthTech TouchPoints event (17/10/2024): VUB and UZ Brussel showcased their HealthTech expertise to companies.

ETRO did a pitch and had a demo booth at the matchmaking fair after the event.

More background info LinkedIn posts:

• https://www.linkedin.com/posts/umcor_vubhealthcampus-umcor-umcorcommunity-activity-7254163276907909120-0AyH?utm_source=share&utm_medium=member_desktop
• https://www.linkedin.com/posts/medvia-be_healthtech-touchpoints-healthinnovation-activity-7254469077698539520-B90z?utm_source=share&utm_medium=member_desktop

On May 25 2022 at 10.30 Mathias Polfliet will defend his PhD entitled “Advances in Groupwise Image Registration”.

Everybody is invited to attend the presentation live (in room Prof. A. Queridozaal, Faculty building Erasmus MC, ‘s Gravendijkwal 230, 3015 CE Rotterdam) or online via this link.

This thesis deals with advances in groupwise image registration. Image registration remains an important task in medical image analysis. Whereas most methods are designed for the registration of two images (pairwise registration), there is an increasing interest in simultaneously aligning more than two images using groupwise registration given the increasing availability of medical imaging data, both at the individual and the population level. Groupwise image registration has shown promise in a number of applications dealing with large quantities of data, among others to increase registration accuracy and robustness, to improve the transformation smoothness and to reduce the methodological bias compared to pairwise registrations. However, directly comparing groupwise registrations to conventional repeated pairwise registrations is difficult due to several confounding factors impacting the algorithm. In this thesis, as a first contribution, we rigorously evaluate two registration methodologies in several experiments and investigate the differences in performance. Secondly, we fill a gap in current literature on efficient (dis)similarity measures for multimodal groupwise image registration. These two contributions are distributed over four chapters.

In Chapter 3, we investigate several registration approaches for the alignment of CT and MRI acquisitions of the mandible in patients with oral squamous cell carcinoma. A comparison is made between rigid and non-rigid approaches with symmetric and asymmetric transformation strategies. The results suggest improved performance in terms of registration accuracy for a symmetric transformation strategy compared to an asymmetric approach, however, the differences were not statistically significant (p=0.054). For this clinical application, we conclude that a rigid registration method is the recommended approach.

In Chapter 4, an investigation is performed on different template images for groupwise registrations based on mutual information. Here, template images are employed as a representative image to compare every image in the group to (in terms of its (dis)similarity). We show that the entropy of the template image can have a counter-intuitive contribution to the global dissimilarity value. Additionally, we show that equivalent performance in terms of registration accuracy can be achieved between groupwise and repeated pairwise approaches.

In Chapter 5, a novel similarity measure is introduced for multimodal groupwise registration. The conditional template entropy measures the negated average of the pairwise conditional entropy of each image of the group and a template image, which is constructed based on principal component analysis. We show improved or equivalent performance in terms of accuracy compared to other state-of-the-art (dis)similarity measures for multimodal groupwise registration and repeated pairwise registration. Furthermore, groupwise registration vastly outperform repeated pairwise registration in terms of transitive error, a measure which can be interpreted as a measure for the consistency of the transformations in a groupwise setting.

In Chapter 6, to further improve on the efficiency of multimodal groupwise registration, we propose a novel dissimilarity measure which is especially adept at registering large groups of images. The dissimilarity measure is formulated as the second smallest eigenvalue of the generalized eigenvalue problem posed in the description of Laplacian eigenmaps. We show little dependence of the measure in terms of computation time with respect to the number of images in the group, and equivalent or improved performance in terms of registration accuracy compared to state-of-the-art groupwise (dis)similarity measures.

To summarize, in this work we evaluate groupwise approaches compared to repeated pairwise approaches and show mostly equivalent performance in terms of registration accuracy and robustness and an improved transitivity for groupwise registration. Furthermore, we recommend to use the proposed dissimilarity measure based on Laplacian eigenmaps for large groups of images given its superior or equivalent registration accuracy compared to other measures but superior scaling in terms of execution time with respect to the number of images in the group.

The paper entitled” Novel Multi-Parametric Sensor System for Comprehensive Multi-Wavelength Photoplethysmography Characterization”, published in the journal MDPI SENSORS in 2023, coauthored by: J.L. Cause, Á. Solé-Morillo, B. Da Silva, J. García-Naranjo, and J. Stiens was awarded with the first prize of the provincial council of scientific health societies of Santiago de Cuba

Abel Díaz Berenguer (Cuba) joined ETRO in 2017 and obtained his PhD in 2021. His father was a Civil engineer, and during his childhood, he spent a lot of time with him in construction works. This triggered his curiosity to build and create things. Since Abel was a kid, he wanted to study ¨something¨ with computers and never had any doubt about studying engineering in informatics sciences.

The PhD program made him feel thoroughly responsible for your research project. Advisors progressively introduce you into the research environment and educate you on digging deeper into fundamental theories by promoting critical thinking. Abel noticed a lack of motivation to participate in dissemination activities that promote science communication. Students also did not feel the need to communicate and to encourage more collaboration between other fellows working in the same or different fields.

Abel enjoyed the Writing Bootcamp of the doctoral Training program very much. The three days course about writing scientific articles offered mainly many good tips about approaching the scientific writing process, which was a great help during the PhD.

Abel has great memories of chats, coffees, and plenty of amusing moments with colleagues. Those moments allowed him to overcome challenging days. The collaboration with close colleagues has been outstanding. Research is a process of knowledge sharing and co-creation with excellent colleagues that became family that stood by my side on long working days and nights.

Abel grew during his PhD into a person with more critical thinking towards solving any problem in life. Be enthusiastic and passionate about your research. Enjoy the learning process with perseverance, dedication, engagement, and curiosity for innovating. Push boundaries and never give up share knowledge and be a team player.

Abel wants to land in an academic environment, help others learn and learn from them. In a position to benefit society, share knowledge and contribute to building a better world for our children.

The programme starts every year in September (typically, the lectures start in the 4th week of September).