Leonid Mill, M. Sc.
- Since 10/2017:
PhD candidate at the Pattern Recognition Lab, FAU
- 10/2014 – 09/2017:
Master studies in Mechatronics, FAU
Thesis:“Conception, implementation and training of artificial neural networks
for control purposes of artificial muscles based on dielectric elastomer actuators”
- 10/2010 – 12/2014
Bachelor studies in Mechatronics, FAU
Thesis:“Development and implementation of an intuitive and gesture based
control software for a robotic application”
- 03/2016 – 09/2017:
Faunhofer IISB, Erlangen
Working student and member of the interdisciplinary student project TechFak EcoCar/ElMo
Tasks: Software development, circuit design, embedded programming
- 10/2015 – 03/2017:
Max Planck Institute for the science of light, Erlangen
Tasks: Software development (Java, C++ and C#)
Advancing osteoporosis medicine by observing bone microstructure and remodelling using a four-dimensional nanoscope
(Third Party Funds Single)Term: April 1, 2019 - March 31, 2025
Funding source: European Research Council (ERC)
Due to Europe's ageing society, there has been a dramatic increase in the occurrence of osteoporosis (OP) and related diseases. Sufferers have an impaired quality of life, and there is a considerable cost to society associated with the consequent loss of productivity and injuries. The current understanding of this disease needs to be revolutionized, but study has been hampered by a lack of means to properly characterize bone structure, remodeling dynamics and vascular activity. This project, 4D nanoSCOPE, will develop tools and techniques to permit time-resolved imaging and characterization of bone in three spatial dimensions (both in vitro and in vivo), thereby permitting monitoring of bone remodeling and revolutionizing the understanding of bone morphology and its function.
To advance the field, in vivo high-resolution studies of living bone are essential, but existing techniques are not capable of this. By combining state-of-the art image processing software with innovative 'precision learning' software methods to compensate for artefacts (due e.g. to the subject breathing or twitching), and innovative X-ray microscope hardware which together will greatly speed up image acquisition (aim is a factor of 100), the project will enable in vivo X-ray microscopy studies of small animals (mice) for the first time. The time series of three-dimensional X-ray images will be complemented by correlative microscopy and spectroscopy techniques (with new software) to thoroughly characterize (serial) bone sections ex vivo.
The resulting three-dimensional datasets combining structure, chemical composition, transport velocities and local strength will be used by the PIs and international collaborators to study the dynamics of bone microstructure. This will be the first time that this has been possible in living creatures, enabling an assessment of the effects on bone of age, hormones, inflammation and treatment.
Critical Review of Processing and Classification Techniques for Images and Spectra in Microplastic Research
In: Applied Spectroscopy 74 (2020), p. 989-1010
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Learning with Known Operators reduces Maximum Training Error Bounds.
In: Nature Machine Intelligence 1 (2019), p. 373-380
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Towards In-Vivo X-Ray Nanoscopy: Acquisition Parameters vs. Image Quality
Workshop on Bildverarbeitung fur die Medizin, 2019 (Lübeck, March 17, 2019 - March 19, 2019)
In: Thomas M. Deserno, Andreas Maier, Christoph Palm, Heinz Handels, Klaus H. Maier-Hein, Thomas Tolxdorff (ed.): Informatik aktuell 2019
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Towards in-vivo X-ray nanoscopy: The effect of motion on image quality
Workshop on Bildverarbeitung fur die Medizin, 2018 (Erlangen, March 11, 2018 - March 13, 2018)
In: Thomas M. Deserno, Andreas Maier, Christoph Palm, Heinz Handels, Klaus H. Maier-Hein, Thomas Tolxdorff (ed.): Informatik aktuell 2018
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