“Signal Processing in the AI era” was the tagline of this year’s IEEE International Conference on Acoustics, Speech and Signal Processing, taking place in Rhodes, Greece.
In this context, Brent de Weerdt, Xiangyu Yang, Boris Joukovsky, Alex Stergiou and Nikos Deligiannis presented ETRO’s research during poster sessions and oral presentations, with novel ways to process and understand graph, video, and audio data. Nikos Deligiannis chaired a session on Graph Deep Learning, attended the IEEE T-IP Editorial Board Meeting, and had the opportunity to meet with collaborators from the VUB-Duke-Ugent-UCL joint lab.
Featured articles:
- De Weerdt, B. et al., “Designing Transformer Networks for Sparse Recovery of Sequential Data Using Deep Unfolding” (https://ieeexplore.ieee.org/abstract/document/10094712)
- Yang X. et al., “Relevance Propagation through Deep Conditional Random Fields” (https://ieeexplore.ieee.org/abstract/document/10095075)
- Stergiou A. et al., “Play it back: Iterative attention for audio recognition” (https://ieeexplore.ieee.org/abstract/document/10096532, developed at the University of Bristol)
Loris Giordano got the best student paper award at the AMAI workshop of MICCAI 2025 for the paper “A modular deep-learning pipeline for automated aorta characterization on CT”, co-authored by Loris Giordano, Jakub Ceranka, Selene De Sutter, Kaoru Tanaka, Gert Van Gompel, Tom Lenaerts, and Jef Vandemeulebroucke.
De Jonge Academie heeft elf nieuwe leden verkozen na een open oproep. Het is ons een genoegen u te mogen melden dat prof. dr. Jeroen Van Schependom de Jonge Academie binnenkort vervoegt als topwetenschapper.
Jeroen Van Schependom (VUB) onderzoekt hoe structurele en functionele beeldvorming van de hersenen kunnen bijdragen aan een betere opvolging van mensen met neurodegeneratieve aandoeningen zoals multiple sclerose en de ziekte van Alzheimer. Daarnaast onderzoekt hij of nieuwe niet-invasieve methodes van hersenstimulatie kunnen helpen om deze ziektes af te remmen
Jeroen blijft lid tot 31 maart 2027. Wij kijken binnen de Jonge Academie erg uit naar samenwerking met hem. Jeroen wordt plechtig geïnaugureerd op woensdagnamiddag 30 maart 2022 om 15u30 in het Paleis der Academiën in Brussel, een gelegenheid waarop wij u van harte uitnodigen. Deze inauguratiezitting is ook een thema-event over Homo Ludens: toeval, serendipiteit en spel(impuls) in de wetenschap — naast een lecture performance, inauguratie en afzwaai stellen we er ook de Maja #7 Homo Ludens voor en het kinderspel
| The RFIC paper title: A 140 GHz T/R Front-End Module in 22 nm FD-SOI CMOS by Xinyan Tang, Johan Nguyen, Giovanni Mangraviti, Zhiwei Zong, and Piet Wambacq was selected as Best Student Paper finalist to the 2021 RFIC Symposium. Therefore, it will be featured in the RFIC 2021 virtual program event Student Papers Showcase, with the opportunity to submit a three minute video to be hosted for all time on IEEE.tv, and inclusion in consideration for the best student paper awards. Well-done! |
An Innoviris-funded project, called eTailor with Treedy’s and ETRO-VUB for full-body scanner that extrapolates your size without you even having to take your clothes off. It will be deployed in the Decathlon shops (and not only) worldwide.
The IP behind this tech is for a part shared IP between VUB and Treedy’s. A VUB-Treedy’s patent was recently accepted covering the technology that enables estimating the body shape under clothing and taking automatically measurements on each scanned person.
eTailor is an example of how an industrial project should run: one could achieve both academic and industrial excellence.
Abel DĂaz 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.
On September 17 2021 at 16.00 Jakub Ceranka will defend his PhD entitled “Advancements in Whole-Body Multi-Modal MRI: Towards Computer-Aided Diagnosis of Metastatic Bone Disease”.
Everybody is invited to attend the online presentation via  this teams link.
Cancer that begins in an organ, such as the lungs, breast or prostate, and then spreads to the bone or other organs, marks the beginning of metastatic disease. The confident detection of metastatic bone disease and the reliable assessment of the tumour load and treatment response is essential to improve patients’ quality of life and increase life expectancy. Magnetic resonance imaging (MRI) has been successfully used for monitoring of metastatic bone disease. Anatomical whole-body sequences offer excellent resolution and sensitivity for the detection of neoplastic cells within the bone marrow. In combination with spatially prealigned functional diffusion-weighted whole-body MRI and apparent diffusion coefficient maps, it allows for focused, efficient, multi-parametric and holistic evaluation of the total tumour volume, diffusion volume and treatment response assessment. One of the major challenges of radiological reading of whole-body MRI in the clinical routine comes from the large amount of data to be reviewed, making lesion detection and quantification demanding for a radiologist, but also prone to error. Additionally, whole-body MR images are often corrupted with multiple spatial and intensity artifacts, which degrade the performance of medical image processing algorithms.
This PhD thesis proposes number of contributions in the medical image processing domain aiming at improving the quality and extending the usability of whole-body multi-modal MRI in the clinical routine. These include spatial groupwise image registration (to align multiple MRI modalities), multi-atlas segmentation (to define the skeleton region of interest), image standardization (to map MRI intensities into comparable ranges) and a deep learning framework for detection and segmentation of metastatic bone disease, as it is pathology of choice for this work. Combined, proposed contributions provide building blocks for a fully automated computer-aided diagnosis (CAD) system for the detection and segmentation of metastatic bone disease using whole-body multi-modal MRI. Finally, an ablation study describing the impact of different CAD system components on detection and segmentation accuracy is provided.