Nils Jacobson defended his Master thesis on 16 February 2021. Congrats!

Nils Jacobson defended his Master thesis in MPCAS at the Chalmers University of Technology on 16 February 2021. Congrats!

Screenshot of Nils Jacobson’s Master Thesis defence.
Title: Vascular Bifurcation Detection in Cerebral CT Angiography Using CNN and Frangi Filters

Segmentation and feature extraction are important tools for analysing and visualizing information in medical image data, particularly in vascular image data which relates to widely spread vascular diseases. Vessel segmentation is extensively featured in research, recently adapting trends in deep learning image processing. This paper aims to develop a vessel bifurcation detection method to support a seed point based segmentation approach. The suggested approach is a combination of classification, with a convolutional neural network (DenseNet), local vessel segmentation, with Frangi filters, and 3D morphological skeletonization. A small data set is produced for network training and evaluation. Results indicate a high classification accuracy which filters problematic samples for the Frangi filter. Thus the combination is able to suggest quality branch seed points under most circumstances. Next step would be to expand the data set to enable further optimization and more rigid evaluation. In any case a combination of a high performance classifier followed by qualitative assessment of local samples show potential.​

​Name of the master programme: MPCAS – Complex Adaptive Systems
Supervisor: Jonna Hellström and Giovanni Volpe
Examiner: Giovanni Volpe, Department of Physics, University of Gothenburg
Opponent: Eva Škvor

Place: Online via Zoom
Time: 16 February, 2021, 16:00

Link: Master thesis presentation Nils Jacobson

Press release on joint research on intercellular communication mechanism by Biological Physics Lab and Soft Matter Lab

The article Intercellular Communication Induces Glycolytic Synchronisation Waves published in PNAS has been featured in the News of the Faculty of Science of Gothenburg University.

Here the links to the press releases:
Swedish: Forskare har knäckt koden för cellkommunikation
English: Researchers have broken the code for cell communication

Giovanni Volpe is committee member at OSA-OMA 2021

Giovanni Volpe is part of the committee of the conference Optical Manipulation and its Applications (OMA), which is part of the OSA Biophotonics Congress: Optics in the Life Sciences.

Optical Manipulation encompasses all areas of manipulation and measurement using light, from optical manipulation of microparticles to photoactivated materials and optogenetics, emphasizing new and developing application areas in biophysics and biomedicine.

The categories of topics in the conference are Optical Manipulation in Biophysics and Biomedicine, Optical Manipulation Fundamentals, Optical Manipulation Applications, and Alternative Manipulation Techniques.

The conference will be held online 12-16 April 2021.

Online seminar by G. Volpe at Indian Institute of Science Education and Research (IISER), Pune, India

Deep learning for microscopy and optical trapping
Giovanni Volpe
21 January 2021, 16:30 CEST
Online
Invited seminar for Indian Institute of Science Education and Research (IISER), Pune, India

After a brief overview of artificial intelligence, machine learning and deep learning, I will present a series of recent works in which we have employed deep learning for applications in photonics and active matter. In particular, I will explain how we employed deep learning to enhance digital video microscopy, to estimate the properties of anomalous diffusion, to characterize microscopic force fields, to improve the calculation of optical forces, and to characterize nanoparticles. Finally, I will provide an outlook for the application of deep learning in photonics and active matter.

Falko Schmidt defended his PhD Thesis in Physics on 15 January 2021. Congrats!

Falko Schmidt defended his PhD Thesis in Physics on Friday, 15 January 2021. Congrats!

The disputation took place at 9 a.m., in PJ salen, Fysikgården.
Falko Schmidt’s opponent, Peer Fischer, gave an introductory presentation with title “Microswimmers and motile active matter”.

Link: http://hdl.handle.net/2077/66807

From Falko Schmidt’s PhD Thesis.
Title: Active Matter in a Critical State: From passive building blocks to active molecules, engines and droplets

The motion of microscopic objects is strongly affected by their surrounding environment. In quiescent liquids, motion is reduced to random fluctuations known as Brownian motion. Nevertheless, microorganisms have been able to develop mechanisms to generate active motion. This has inspired researchers to understand and artificially replicate active motion. Now, the field of active matter has developed into a multi-disciplinary field, with researchers developing artificial microswimmers, producing miniaturized versions of heat engines and showing that individual colloids self-assemble into larger microstructures. This thesis taps into the development of artificial microscopic and nanoscopic systems and demonstrates that passive building blocks such as colloids are transformed into active molecules, engines and active droplets that display a rich set of motions. This is achieved by combining optical manipulation with a phase-separating environment consisting of a critical binary mixture. I first show how simple absorbing particles are transformed into fast rotating microengines using optical tweezers, and how this principle can be scaled down to nanoscopic particles. Transitioning then from single particles to self-assembled modular swimmers, such colloidal molecules exhibit diverse behaviour such as propulsion, orbital rotation and spinning, and whose formation process I can control with periodic illumination. To characterize the molecules dynamics better, I introduce a machine-learning algorithm to determine the anomalous exponent of trajectories and to identify changes in a trajectory’s behaviour. Towards understanding the behaviour of larger microstructures, I then investigate the interaction of colloidal molecules with their phase-separating environment and observe a two-fold coupling between the induced liquid droplets and their immersed colloids. With the help of simulations I gain a better physical picture and can further analyse the molecules’ and droplets’ emergence and growth dynamics. At last, I show that fluctuation-induced forces can solve current limitations in microfabrication due to stiction, enabling a further development of the field towards smaller and more stable nanostructures required for nowadays adaptive functional materials. The insights gained from this research mark the path towards a new generation of design principles, e.g., for the construction of flexible micromotors, tunable micromembranes and drug delivery in health care applications.

Fast and Accurate Nanoparticle Characterization Using Deep-Learning-Enhanced Off-Axis Holography published in ACS Nano

Phase and amplitude signals from representative particles for testing the performance of the Deep-learning approach

Fast and Accurate Nanoparticle Characterization Using Deep-Learning-Enhanced Off-Axis Holography
Benjamin Midtvedt, Erik Olsén, Fredrik Eklund, Fredrik Höök, Caroline Beck Adiels, Giovanni Volpe, Daniel Midtvedt
ACS Nano 15(2), 2240–2250 (2021)
doi: 10.1021/acsnano.0c06902
arXiv: 2006.11154

The characterisation of the physical properties of nanoparticles in their native environment plays a central role in a wide range of fields, from nanoparticle-enhanced drug delivery to environmental nanopollution assessment. Standard optical approaches require long trajectories of nanoparticles dispersed in a medium with known viscosity to characterise their diffusion constant and, thus, their size. However, often only short trajectories are available, while the medium viscosity is unknown, e.g., in most biomedical applications. In this work, we demonstrate a label-free method to quantify size and refractive index of individual subwavelength particles using two orders of magnitude shorter trajectories than required by standard methods, and without assumptions about the physicochemical properties of the medium. We achieve this by developing a weighted average convolutional neural network to analyse the holographic images of the particles. As a proof of principle, we distinguish and quantify size and refractive index of silica and polystyrene particles without prior knowledge of solute viscosity or refractive index. As an example of an application beyond the state of the art, we demonstrate how this technique can monitor the aggregation of polystyrene nanoparticles, revealing the time-resolved dynamics of the monomer number and fractal dimension of individual subwavelength aggregates. This technique opens new possibilities for nanoparticle characterisation with a broad range of applications from biomedicine to environmental monitoring.

Giovanni Volpe awarded new ERC Consolidator Grant

ERC logo.
Giovanni Volpe has been awarded a new European Research Council (ERC) Consolidator Grant on Wednesday, December 9th 2020.

The title of his project is “Microscopic Active Particles with Embodied Intelligence”.

Active particles and active matter research tries to understand and replicate the characteristics of living microorganisms in artificial systems. Over billions of years of evolution, living organisms have developed complex strategies to survive and thrive. The artificial active particles are still incapable of autonomous information processing.

Giovanni Volpe’s project aims to address three main challenges in the current research on active matter:

  • Make active particles capable of autonomous information processing.
  • Optimize the behavioral strategies of individual active particles.
  • Optimize the interactions between active particles.

Links
Giovanni Volpe awarded new ERC Consolidator Grant
Official press release (ERC): CoG Recipients 2020
14 forskare verksamma i Sverige får ERC Consolidator grant

Digital Christmas Lunch 2020, Soft Matter Lab and Biological Physics Lab

A screenshot from the Soft Matter Lab and Biological Physics Lab’s Digital Christmas Lunch 2020.
On November 25, the members of the Soft Matter Lab and of the Biological Physics Lab joined for the Digital Christmas Lunch 2020.

This activity has been held in substitution of the traditional Physics Department Christmas Lunch, which this year cannot take place in the usual format because of the ongoing coronavirus epidemic.

After the usual group meeting, which is held online on Zoom since the beginning of March 2020, the two groups shared a common lunch, in respect of the current recommendations of the Folkhälsomyndigheten, which do not allow public gatherings with more than 8 people.

Several group members joined from their homes. The group members involved in experimental work, who, in any case, had to be present in the respective labs, joined the group lunch from various rooms in Soliden, to comply with the current rules of social distancing.

Screenshots:

Lecture by G. Volpe: Graph Theory Concepts, 25 November 2020

On 25 November 2020, Giovanni Volpe gave an online lecture on Graph Theory Concepts, in the scope of Karolinska Institute graduate course 3064: Imaging in Neuroscience: With a focus on structural MRI methods

The lecture is published online on youtube.

Link:
Imaging in Neuroscience: Graph Theory Concepts