Ivo Matteo Baltruschat, M.Sc.

Universitätsklinikum Hamburg-Eppendorf (UKE)
Sektion für Biomedizinische Bildgebung
Lottestraße 55
2ter Stock, Raum 213
22529 Hamburg

Technische Universität Hamburg (TUHH)
Institut für Biomedizinische Bildgebung
Gebäude C, Raum 2.019
Schwarzenbergstraße 95C
21073 Hamburg

Tel.: 040 / 7410 25813
E-Mail: i.baltruschat(at)uke.de
GitHub: https://github.com/Ivo-B

Research Interests

Machine Learning            Medical Image Processing            Computer Vision            Deep Learning

My current research covers the automatic analysis of medical x-ray images using machine learning methods. Our objective is to apply deep learning methods to high-resolution medical x-ray images. In the long-term, we are pursuing the goal to employ deep learning methods in order to find patterns between medical reports and medical x-ray images that will help to push the state-of-the-art in computer-aided diagnosis for chest x-ray images.

Curriculum Vitae

Ivo Baltruschat studied Information and Electrical Engineering at the University of Applied Sciences, Hamburg between 2010 and 2014. In 2016, he finished his Master of Science in medical engineering science at the Universität zu Lübeck with his thesis on Deep Learning for Advanced Medical Applications. Currently, he is a PhD student in the group of Tobias Knopp and his research covers Deep Learning methods for automatic analysis of clinical X-ray images.

Student Project

If you are looking for a supervisor for a student project (B.Sc./M.Sc.), please don't hesitate to contact me. In general, I am always looking for highly motivated students to work on medical image analysis problems with deep learning.

Open topics:
  • Multi-View Classification
  • Pre-Processing for Deep Learning
  • Generative Adversarial Network (multiple applications)

Awards

  • Poster Award SPIE Medical Imaging 2018

     awarded with the Honorable Mention Poster Award for my contribution:

    "Orientation Regression in Hand Radiographs: A Transfer Learning Approach"

    at the SPIE Medical Imaging Houston, USA, 02/17/2018.

Publications

  • I. M. Baltruschat, L. Steinmeister, H. Ittrich, G. Adam, H. Nickisch, A. Saalbach, J. von Berg, M. Grass, T. Knopp (2019). When does Bone Suppression and Lung Field Segmentation Improve Chest X-Ray Disease Classification?. International Symposium on Biomedical Imaging (ISBI 2019) [BibTex]

  • I. M. Baltruschat, L. Steinmeister, H. Ittrich, G. Adam, H. Nickisch, A. Saalbach, J. von Berg, M. Grass, T. Knopp (2019). Abstract: Does Bone Suppression and Lung Detection Improve Chest Disease Classification?. Bildverarbeitung für die Medizin (BVM 2019) [BibTex]

  • I. M. Baltruschat, F. Griese, P. Szwargulski, R. Werner, T. Knopp (2019). Wrestling the Devil of Wasting Time: MPI System Matrix Recovery by Deep Learning. 9th International Workshop on Magnetic Particle Imaging (IWMPI 2019) 109-110. [Abstract] [BibTex]

  • I. M. Baltruschat, M. Grass, A. Saalbach, H. Nickisch, J. von Berg, L. Steinmeister, H. Ittrich, T. Knopp, G. Adam (2019). Neuronale Netze zur Pathologiedetektion bei Röntgenthoraxuntersuchungen: Verbesserung durch intelligente Vorverarbeitung. Deutscher Röntgenkongress (RöKo 2019) [BibTex]

  • M. Grass, I. M. Baltruschat, A. Saalbach, H. Nickisch, J. von Berg, G. Adam, L. Steinmeister, H. Ittrich, T. Knopp (2019). Effect of Advanced Image Pre-Processing for Multi-Label Chest X-Ray Classification. European Congress of Radiology (ECR 2019) [BibTex]

  • H. Ittrich, I. M. Baltruschat, L. A. Steinmeister, M. Grass, A. Saalbach, T. Knopp, G. Adam, H. Nickisch (2018). Effect of Inter-Observer Variability on Deep Learning in Chest X-Rays. Radiological Society of North America (RSNA 2018) [BibTex]

  • I. M. Baltruschat, A. Saalbach, M. P. Heinrich, H. Nickisch, S. Jockel (2018). Orientation Regression in Hand Radiographs: A Transfer Learning Approach. SPIE Medical Imaging: Image Processing (SPIE 2018) 10574-67. [BibTex]

  • I. M. Baltruschat, H. Nickisch, M. Grass, T. Knopp, A. Saalbach (2018). Patient data adapted deep learning for multi-label chest X-ray classification. Radiological Society of North America (RSNA 2018) [BibTex]

  • I. M. Baltruschat, H. Nickisch, M. Grass, T. Knopp, A. Saalbach (2018). Comparison of Deep Learning Approaches for Multi-Label Chest X-Ray Classification. arXiv preprint arXiv:1803.02315 [BibTex]

  • N. Gessert, T. Sentker, F. Madesta, R. Schmitz, H. Kniep, I. M. Baltruschat, R. Werner, A. Schlaefer (2018). Skin Lesion Diagnosis using Ensembles, Unscaled Multi-Crop Evaluation and Loss Weighting. arXiv preprint arXiv:1808.01694 [BibTex]

  • I. M. Baltruschat, M. Hensel, M. P. Heinrich (2016). Automatic Orientation Detection of Hand Structures in Digital X-Ray Images. Student Conference Medical Engineering Science, Lübeck Germany, Publisher Infinite Science Publishing [BibTex]