• Den Dolech 2

    5612 AZ Eindhoven


  • P.O.Box 513, Department of Electrical Engineering

    5600 MB Eindhoven


Organization profile

Introduction / mission

Clinical relevance is our commitment, achieved through close collaboration with selected clinical/industrial partners and advisors.

Organisational profile

The Biomedical Diagnostics (BM/d) Research Laboratory develops algorithms for the interpretation of biomedical signals and data acquired with a variety of sensors, ranging from ultrasound and magnetic resonance imaging, up to electrophysiological and photoplethysmographic recording. The lab positions itself on the edge between data-driven and physics-driven analysis through a continuous effort towards understanding the application domain and modeling the full measurement chain: (patho)physiological sources, sensing physics, and signal acquisition. To this end, research is carried out in tight collaboration with our clinical and industrial partners. The main application areas are oncology, cardiovascular, gynecology-perinatology, sleep, and neuromuscular research. The lab is chaired by Prof. Mischi, supported by a multidisciplinary team integrating expertise in modeling (Dr. Turco), Bayesian inference (Dr. Vullings), and machine learning (Dr. van Sloun).

Fingerprint Dive into the research topics where Biomedical Diagnostics Lab is active. These topic labels come from the works of this organisation's members. Together they form a unique fingerprint.

Prostatic Neoplasms Medicine & Life Sciences
Electrocardiography Engineering & Materials Science
Ultrasonography Medicine & Life Sciences
Ultrasonics Engineering & Materials Science
Monitoring Engineering & Materials Science
Sleep Medicine & Life Sciences
Fetal Heart Rate Medicine & Life Sciences
Photoplethysmography Engineering & Materials Science

Network Recent external collaboration on country level. Dive into details by clicking on the dots.

Research Output 2000 2020

Artificial Intelligence
Artificial intelligence
Prostatic Neoplasms
Imaging techniques

Automated discomfort detection for premature infants in NICU using time-frequency feature-images and CNNs

Sun, Y., Kommers, D., Tan, T., Wang, W., Long, X., Shan, C., van Pul, C., Aarts, R. M., Andriessen, P. & de With, P. H. N., 2020, SPIE Medical Imaging. SPIE, 11314-153

Research output: Chapter in Book/Report/Conference proceedingConference contributionAcademicpeer-review

Optical flows
12 Downloads (Pure)

Automated multiparametric localization of prostate cancer based on B-mode, shear-wave elastography, and contrast-enhanced ultrasound radiomics

Wildeboer, R. R., Mannaerts, C. K., van Sloun, R. J. G., Budäus, L., Tilki, D., Wijkstra, H., Salomon, G. & Mischi, M., Feb 2020, In : European Radiology. 30, 2, p. 806-815 10 p.

Research output: Contribution to journalArticleAcademicpeer-review

Open Access
Elasticity Imaging Techniques
Prostatic Neoplasms
ROC Curve
Area Under Curve


Academy Van Leersum Grant

Simona Turco (Recipient), 2019

Prize: KNAWOtherScientific

The Netherlands
National Archives

Best Poster Award 2017 in New Directions - Contrast Ultrasound

Rogier Wildeboer (Recipient), 20 Jan 2017

Prize: OtherCareer, activity or publication related prizes (lifetime, best paper, poster etc.)Scientific

Best Poster Award 2018 in New Directions - Contrast Ultrasound

Rogier Wildeboer (Recipient), 19 Jan 2018

Prize: OtherCareer, activity or publication related prizes (lifetime, best paper, poster etc.)Scientific

Activities 2002 2019

Annual IEEE EMBS Benelux Chapter Symposium

Anouk van Diepen (Participant)
28 Nov 2019

Activity: Participating in or organising an event typesConferenceScientific

National Day on Biomedical Engineering: Artificial Intelligence in Medicine

Anouk van Diepen (Participant)
28 Nov 201929 Nov 2019

Activity: Participating in or organising an event typesConferenceScientific

2019 IEEE International Ultrasonics Symposium, IUS 2019

Rogier R. Wildeboer (Participant)
6 Oct 20199 Oct 2019

Activity: Participating in or organising an event typesConferenceScientific

Student theses

Adversarial deep learning in super resolution ultrasound

Author: Jeukendrup, K., 31 Jan 2019

Supervisor: van Sloun, R. (Supervisor 1)

Student thesis: Master

Estimation of acoustical coefficient of nonlinearity

Author: Zeng, Y., 24 May 2018

Supervisor: Mischi, M. (Supervisor 1) & Wijkstra, H. (Supervisor 2)

Student thesis: Master

Machine learning for classification of uterine activity during IVF cycles

Author: Bakkes, T., 13 Dec 2018

Supervisor: Mischi, M. (Supervisor 1), Sammali, F. (Supervisor 2) & Schoot, B. (Supervisor 2)

Student thesis: Master