Johan Stiens participated as Belgian representative of BSMBEC-NCBME this morning to the “European Parliament Interest Group on Biomedical Engineering”

The fourth meeting with European Parliament Members took place in hybrid mode on March 21, 2023, on the premises of the European Parliament hosted by MEP Stelios Kympouropoulos with the support of the European Alliance of Medical and Biological Engineering and Science (EAMBES) as part of a week dedicated to the role of technology in health. The event was entitled: “Pandemic Management and Preparedness – Telemedicine and the Role of Innovative Technologies in Securing a Safer Future”.  Please find here the final Agenda of the meeting.

On January 23rd 2024 at 16.30, Ine Dirks will defend their PhD entitled “COMPUTER-AIDED DIAGNOSIS AND DECISION SUPPORT USING MEDICAL IMAGE ANALYSIS – CONTRIBUTIONS TO MALIGNANT MELANOMA AND COVID-19”.

Everybody is invited to attend the presentation at the Room I.0.02, or digitally via this link.

In medicine, the high volume of available data and the expanded number of treatment options have rendered it increasingly complex to determine the appropriate therapy for a specific patient. Precision medicine is a promising and emerging approach to tailor disease prevention and treatment by considering individual patient characteristics. Computer-aided diagnosis (CAD) systems can support physicians by performing fast, objective and reproducible medical image analyses and by extracting parameters that allow for more personalised disease assessment and response prediction. These features can then be used in a clinical decision support (CDS) system to guide therapeutic decisions. In this work, we investigate CAD and CDS methods for two pathologies: malignant melanoma and COVID-19.

Malignant melanoma is the most lethal form of skin cancer. Treatment planning and monitoring are generally performed using combined positron emission tomography/computed tomography (PET/CT) with fluorine-18 fluorodeoxyglucose ([18F]FDG) and regular testing of blood values. Recently, survival chances have increased due to advances in immunotherapy and targeted therapies. Nonetheless, a considerable part of this population demonstrates progressive disease. If patients with a poor prognosis can be identified before the start of therapy, a more aggressive treatment pathway could be considered to improve the survival chances.

A fully automated system was developed for lesion detection and segmentation on whole-body [18F]FDG PET/CT to extract information on the tumour load from the imaging data. We further demonstrated the feasibility of using these automatically derived imaging features in survival analysis through a comparative study with the manual method. The automated approach led to very similar results and could therefore enable the use of these parameters in clinical routine and future clinical trials.

A second pathology investigated is COVID-19, which presented great challenges for the medical sector worldwide. During the pandemic, intensive care units were overwhelmed and proper resource allocation became problematic. During the periods of high prevalence, there was an urgent need for computer-aided systems to support decisions in diagnosis, treatment and resource allocation.

In a large research collaboration, automated tools were developed to alleviate the situation. The resulting methods allow to segment lung lesions and extract relevant parameters. In addition, a model was developed to predict disease severity at one month. Its performance was validated in the context of an international challenge and proved robust through evaluation on different, multicentre datasets.

Our work demonstrated the potential of CAD and CDS systems in the field but also revealed pitfalls and shortcomings. Several challenges remain before such systems can be used readily in clinical routine, including thorough validation and medical certification. Still, important contributions were made to help in the shift towards precision medicine.

You van visit the LEGO urban planner again and design your climate-resilient city at “Dag van de Wetenschap” (Science Day) on Sunday 26 November at Muntpunt.

The program is organised to accommodate your scientific background and future-oriented academic interests – developing the necessary Computer Science and Data Science skills by complementing your primary field of expertise. Above all that, we offer a wide variety of highly specialised elective courses;

The Master of Applied Computer Science provides a broad education in data science and engineering with focus on generic smart systems design, complemented with elective minors in digital health, smart cities, environmental informatics, and business intelligence. The accumulated knowledge will give rise to an ICT engineer, capable to design systems of systems and apply analytics on the heterogeneous data obtained by such systems.

Kick-off of the VLIR-UOS Short Initiative project NEST: Non-intrusive devices for Telemedicine.

The event occurred at the Escuela Superior Politécnica del Litoral (ESPOL) in Guayaquil (Ecuador) on the 20th of January. The kick-off event consisted of a seminar describing the project’s objectives for a broad audience. In the afternoon, training about the PPG EduKit took place for students, technical assistants, and professors of the engineering programs at the ESPOL.

On May 9 2022 at 14.00 Zhiwei Zong will defend his PhD entitled “DESIGN OF VCOs AND PAs IN 22 NM FD-SOI FOR 5G MM-WAVE COMMUNICATIONS”.

Everybody is invited to attend the presentation online via this TEAMS link.

The use of spectrum in the millimeter-wave (mm-Wave) frequency range is considered as a key enabler to continue the insatiable demand for increased wireless data capacity. This spectrum will be adopted in the 5G wireless communication standard. To obtain a high integration degree for the implementation of 5G mm-Wave transceivers, advanced CMOS is the preferred technology. The higher operating frequency, compared to 4G, poses more design challenges on the key building blocks of a transceiver. This PhD thesis focuses on the design of the two key building blocks in a 5G mm-Wave transceiver, namely a voltage-controlled oscillator (VCO) and a power amplifier (PA). All building blocks designed in this PhD work are operating in the 20-30 GHz frequency region. All building blocks have been designed in a 22nm fully-depleted silicon-on-insulator (FD-SOI) CMOS technology.

First, a modified transformer-feedback VCO (TF-VCO) with a sourcebridging capacitor (Cs) is introduced. Thanks to the use of Cs, the phase noise (PN) in the 1/f2 and 1/f3 regions are both improved compared to earlier published TF-VCOs. The origin of the PN improvement by the use Cs is explained in this thesis. It is seen that with Cs we can improve the symmetry of the waveform of the voltage over the tank of the VCO. Also, with Cs the effective quality factor of the transformer can be increased, which also reduces phase noise. These theoretical investigations are proven with measurement results. With a second design, an LC-VCO design, another key design challenge is tackled, namely the suppression of flicker noise upconversion. A 22-29GHz voltage-biased LC-VCO is designed and implemented to suppress this flicker noise upconversion by using a flicker noise filtering technique. A self-coupled inductor and a common-centroid capacitor bank layout are proposed in this design to guarantee a good flicker noise suppression over the frequency tuning range.

Next, two 28GHz PAs are designed and implemented for 5G mm-Wave communications. The first PA focuses on generation of a high output power (Pout) with a high linearity. This is achieved in a first design that uses a two-way current combiner and an output stage that uses stacking of transistors. The stack of three transistors used in this design enables the generation of a high output power without overstressing the core devices. The second PA focuses on the power back-off (PBO) efficiency enhancement. This is important for communication with a high spectral efficiency: high-order modulation requires to operate at a relatively large back-off from the saturation level. The design is based on the Doherty architecture. By merging lumped passive components into a transformer, a transformer-based Doherty PA with a compact power combiner is obtained, achieving Doherty load modulation with a compact footprint. This design has the highest power density and ITRS PA figure-of-merit (FOM) among the published mm-wave Doherty PAs.