Periodic Reporting for period 1 - HoloZcan (Deep Learning Powered Holographic Microscopy for Biothreat Detection on Field)
Periodo di rendicontazione: 2021-05-01 al 2022-10-31
One of the challenges that first responders face is the limited capability to detect airborne biological threats. Current methods for detecting biological agents can be time-consuming, labor-intensive, and require specialized equipment and trained personnel. This can make it difficult for first responders to identify biological threats quickly and accurately in the field. This is particularly challenging in situations where time is of the essence and a prompt response is required to protect public health and safety. The EU-funded HoloZcan project aims to address this challenge by developing a high-resolution, portable detection system that can automatically classify pathogens and air particles.
Being able to detect and classify airborne biological threats in a timely manner is important for society because it helps to protect public health and safety. Early detection and identification of biological agents can allow for a prompt response and prevent the spread of disease. It also allows for the implementation of control measures, such as quarantine and decontamination procedures. This is especially important in the context of potential bioterrorism attacks. Rapid and accurate detection and classification also enable more targeted and effective responses, reducing unnecessary disruption and costs.
Overall objectives:
The overall aim is to enhance the capability of CBRN practitioners in detecting and classifying pathogens and particles in real time and in various contexts. The project also aims to address identified shortcomings in current bio-threat agent detection approaches and respond to the needs of European practitioners.
The project aims to demonstrate the versatility and technical feasibility of the HoloZcan technique for a wide range of applications. It addresses the specific needs of European practitioners and technological gaps identified by the ENCIRCLE project, as well as shortcomings of current bio-threat agent detection approaches.
Being able to detect and classify airborne biological threats in a timely manner is important for society because it helps to protect public health and safety. Early detection and identification of biological agents can allow for a prompt response and prevent the spread of disease. It also allows for the implementation of control measures, such as quarantine and decontamination procedures. This is especially important in the context of potential bioterrorism attacks. Rapid and accurate detection and classification also enable more targeted and effective responses, reducing unnecessary disruption and costs.
Overall objectives:
The overall aim is to enhance the capability of CBRN practitioners in detecting and classifying pathogens and particles in real time and in various contexts. The project also aims to address identified shortcomings in current bio-threat agent detection approaches and respond to the needs of European practitioners.
The project aims to demonstrate the versatility and technical feasibility of the HoloZcan technique for a wide range of applications. It addresses the specific needs of European practitioners and technological gaps identified by the ENCIRCLE project, as well as shortcomings of current bio-threat agent detection approaches.
An early prototype of the HoloZcan system has been developed as a laboratory tool. It can be used for experiments and the building of background databases. The design and optimization of an advanced prototype has also been carried out, which will be deployed at the Pasteur Institute in February 2023. Additionally, the sampler subsystem has been extensively tested and integration between the sampler and the imaging system is currently in progress. The project is also working on developing a conceptual design for a smaller and more affordable/fieldable version of the detection system. This design will be developed during the remainder of the project.
The HoloZcan project has made progress in developing algorithms for the detection system, constantly updating and improving them through the analysis of state-of-the-art techniques for holographic image processing. The focus of the algorithm development has been on digital holographic image reconstruction, detection, and classification. The project team has also carried out simulations of holograms in order to have a realistic data set to investigate the representation of holographic features, train models, assist in system design and optimization and compare different configuration parameters.
The project has also established an iterative, test-driven approach since the beginning of the project to connect the complex workflows between the digital holographic microscope (DHM) prototype development, data analysis algorithm development, data collection and demonstration. The project team has also put significant effort into building an interdisciplinary bridge between experts from various fields such as microbiology, hardware engineering, database building, data analysis and communication experts. This approach allows for a comprehensive approach to the project, ensuring that all aspects are properly addressed and integrated.
The HoloZcan project has made progress in developing algorithms for the detection system, constantly updating and improving them through the analysis of state-of-the-art techniques for holographic image processing. The focus of the algorithm development has been on digital holographic image reconstruction, detection, and classification. The project team has also carried out simulations of holograms in order to have a realistic data set to investigate the representation of holographic features, train models, assist in system design and optimization and compare different configuration parameters.
The project has also established an iterative, test-driven approach since the beginning of the project to connect the complex workflows between the digital holographic microscope (DHM) prototype development, data analysis algorithm development, data collection and demonstration. The project team has also put significant effort into building an interdisciplinary bridge between experts from various fields such as microbiology, hardware engineering, database building, data analysis and communication experts. This approach allows for a comprehensive approach to the project, ensuring that all aspects are properly addressed and integrated.
The HoloZcan project aims to progress beyond the state of the art by developing a novel holographic microscopy and imaging technology for rapid and cost-efficient screening of potential biological threats and unknown, potentially dangerous substances. This technology will be combined with methods of artificial intelligence and machine learning which will allow for the automatic classification of pathogens and particles, making it a highly efficient and accurate detection system. The use of holographic microscopy and imaging technology, in combination with AI and machine learning, is expected to significantly improve the current methods of bio-aerosol sensing and measurement, and address some of the challenges faced by CBRN practitioners in detecting and responding to potential biological threats.
If the ability of CBRN professionals to detect and measure bioaerosols (ambient and exhaled) is increased, it could have a significant impact in several areas. Some potential benefits include:
• Enhanced public safety: The improved detection and measurement of bioaerosols will help to identify and respond to potential biological threats more quickly and effectively, thereby increasing the overall safety of the public.
• Increased efficiency and cost saving in emergency response: The use of portable, high-resolution detection systems for bioaerosols will increase the efficiency of emergency response efforts, enabling CBRN professionals to quickly and accurately identify and respond to potential threats in a variety of settings.
• Improved intelligence gathering: The ability to detect and measure bio-aerosols in the field can also provide valuable intelligence on the spread of bio-aerosols, which can be used to improve future response efforts and develop countermeasures.
If the ability of CBRN professionals to detect and measure bioaerosols (ambient and exhaled) is increased, it could have a significant impact in several areas. Some potential benefits include:
• Enhanced public safety: The improved detection and measurement of bioaerosols will help to identify and respond to potential biological threats more quickly and effectively, thereby increasing the overall safety of the public.
• Increased efficiency and cost saving in emergency response: The use of portable, high-resolution detection systems for bioaerosols will increase the efficiency of emergency response efforts, enabling CBRN professionals to quickly and accurately identify and respond to potential threats in a variety of settings.
• Improved intelligence gathering: The ability to detect and measure bio-aerosols in the field can also provide valuable intelligence on the spread of bio-aerosols, which can be used to improve future response efforts and develop countermeasures.