• Den Dolech 2

    5612 AZ Eindhoven

    Netherlands

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

    5600 MB Eindhoven

    Netherlands

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.

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

    Research Output

    A mobile app for longterm monitoring of narcolepsy symptoms: design, development, and evaluation

    Quaedackers, L., de Wit, J., Pillen, S., van Gilst, M., Batalas, N., Lammers, G. J., Markopoulos, P. & Overeem, S., 7 Jan 2020, In : JMIR Mhealth and Uhealth. 8, 1, 14 p., e14939.

    Research output: Contribution to journalArticleAcademicpeer-review

    Open Access
    File
  • 10 Downloads (Pure)
  • 2 Citations (Scopus)

    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, Vol. 11314. 8 p. 11314

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

  • Prizes

    Academy Van Leersum Grant

    Simona Turco (Recipient), 2019

    Prize: KNAWOtherScientific

  • 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

    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

    Annual IEEE EMBS Benelux Chapter Symposium

    Anouk van Diepen (Participant)
    28 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