Introducing AI for image analysis - How to be successful? PART IV

Termine Dauer 1 Tag

In Online Webinar am 16.09.2021



#digitization #artificialintelligence #digitalpathology #aisolutions #imageanalysis #deeplearning #machinelearning #tissueanalysis #neuroaxonalpathology #neuroregeneration #traumatology

Computational pathology, or the use of Artificial Intelligence (AI) in the field of histopathology, holds significant potential for healthcare. For many of us, this emerging, fast-developing discipline comes with many interrogations. For pathologists, it is a change process, as they will see their working practices evolve in the coming years and decades.

At PreciPoint, we believe that communication plays a crucial part in demystifying Artificial Intelligence by bringing computer science and pathology closer together. We also believe that no pathologist must become a computer scientist in order to work with AI.

With our new series of Webinars Pathology meets Technology, we are creating a platform for both communities to learn from each other and create more synergies.


Introducing AI for image analysis - How to be successful?

In this 4-part webinar series, we provide a practical framework to pathology professionals who want to start using artificial intelligence in their research work but do not quite know where to start.

Key learnings:

•         Understand the key concepts of AI development

•         Know what needs to be in place before your start with AI

•         Know how to define your requirements and what kind of AI solution to look for

•         Understand the process of developing your own analysis

During the final webinar, we will look at a recent AI-based application in neuro-regeneration at the Ludwig Boltzmann Institute in Vienna.

Please register for the webinar series. You may attend all webinars or select any individual webinar you wish to attend.


Part 1 – September 13, 2021 17:00 CEST / 11:00 EDT / 23:00 CST (30 min)

·        Key concepts of AI

·        Is my organization ready for AI? Pre-requisites and considerations

Image analysis is a process, not a piece of software. We explain how to start the process in your organization, outline the AI development cycle and explain the key buzzwords such as deep learning, neural network, explainability, etc.

Part 2 – September 14, 2021 17:00 CEST / 11:00 EDT / 23:00 CST (30 min)

·        Choosing the right analysis solution: Defining your requirements

New AI solutions are coming out every day but not every solution is right for you. We discuss the key questions you should ask yourself as you define your objectives and requirements for an AI solution.

Part 3 – September 15, 2021 17:00 CEST / 11:00 EDT / 23:00 CST (30 min)

·        Developing your own analysis: Best-practices and challenges

Looking a little closer into AI development, we review the training and validation process, highlight some key challenges and how you can overcome them.

Part 4 – September 16, 2021 17:00 CEST / 11:00 EDT / 23:00 CST (30 min)

·        Axon recognition for quantitative analysis of axonal regeneration after peripheral nerve injury

We explore a novel use case of AI in neuro-regeneration at the Ludwig Boltzmann Institute for Experimental and Clinical Traumatology in collaboration with KML Vision.


Speakers for this event:

Birgit Müller

Head of Business Development

PreciPoint GmbH



Ms. Birgit Müller is the Head of Business Development at PreciPoint, a creator and provider of digital microscopy solutions for laboratories. In her function, Birgit is responsible for customer projects implementing digital solutions with all the changes needed both on the side of the lab as well as the technology. Ms. Müller has extensive experience with digitization projects both in laboratories as well as in industrial companies having worked in management consulting before joining PreciPoint.


Philipp Kainz

Founder and CEO

KML Vision


Philipp is a co-founder of KML Vision. Formerly overseeing product development as CTO, he now holds the position of the CEO since 2020. He studied Health Care Engineering & eHealth at Graz University of Applied Sciences. In 2016, he received his PhD from the Medical University of Graz and did his PostDoc on Deep Learning in Medical Image Analysis with the Ludwig Boltzmann Institute for Clinical-Forensic Imaging. His main motivations are accelerating the transfer from technological breakthroughs to business cases and creating value by providing state-of-the-art technology based on Artificial Intelligence.


David Hercher

Head of Neuroregeneration Group

Ludwig Boltzmann Institute for Experimental and Clinical Traumatology 



David Hercher studied Molecular Biology at the University of Vienna and finished his Dr. scient. Med at the Medical University of Vienna. His main research focus is the investigation of regenerative processes after injuries with special emphasis on the nervous system. His group works on the elucidation of modes of action of mechanical stimuli on nerve tissue as well as on improving outcomes after peripheral nerve injuries with segmental tissue loss. Furthermore, he works on non-viral gene therapy and novel imaging modalities and their application in the field of regenerative medicine.

Um die Funktionalität dieser Website für Sie optimal zu gestalten, verwenden wir Cookies. Um diese Website vollumfänglich nutzen zu können, stimmen Sie der Verwendung von Cookies zu. Mehr erfahren.