Claudia Lindner


Personal profile


I am a Sir Henry Dale Fellow and Senior Research Fellow who is passionate about making a difference to people’s lives - with a focus on translating digital healthcare solutions into clinical practice. 

My research interests are in the automated analysis of medical images to study, diagnose and manage musculoskeletal disorders. I use methods from computer vision, machine learning and data science to develop accurate systems for outlining and analysing structures in widely used medical images such as radiographs. 

My multidisciplinary fellowship project aims to develop a software tool to automatically analyse radiographic image information, clinical and patient-reported data to improve the management and outcome of knee replacement surgery, and to develop general guidance and strategies on how to bring such a tool into the clinic.

The overall goal of my research is to transform clinically collected image data into useful medical information to benefit healthcare at individual and societal levels.

Please also see my personal website for more details on my research.

In my role as the Translation Lead for the Christabel Pankhurst Institute I focus on making research translation an integral part of health technology research, aiming to facilitate and improve the translation of research findings into benefits for society.


Claudia is a certified IT Specialist in Software Engineering (2002, German Chamber of Commerce and Industry). She received the BSc (2005) and the MSc (2007) degrees in Computer Science, both with distinction, from the Heinrich Heine University Düsseldorf, Germany, and the PhD (2014) degree in Medical Computer Science from the University of Manchester, U.K. Claudia has also obtained a PgC (2006) in International Business and a PgD (2007) in Business Administration from the University of the Sunshine Coast, Australia.

Her career includes over 20 years of experience in the development and application of computational methods working within multi-disciplinary teams (computer science, business, medicine/health) in both industrial and academic settings in Germany, Australia and the U.K. She has won several national and international awards including the 1st prize for the Automated Detection and Analysis for Diagnosis in Cephalometric X-ray Images at the ISBI Grand Challenge event in New York in April 2015, highlighting the state-of-the-art performance of BoneFinder. In 2019, Claudia was awarded Highly Commended at the 2019 L’Oréal-UNESCO UK & Ireland Fellowships for Women in Science programme, and in 2021 she received the Wellcome-Beit Prize for outstanding biomedical researchers. She was elected as a Fellow of the Young Academy of Europe in 2022.

Research interests

Claudia's research interests include medical imaging, computer vision,  and machine learning as well as any form of research into musculoskeletal disorders related to bone shape. She develops robust and accurate systems for locating the outlines of bones and other structures in widely used medical images such as radiographs.

The overall goal of her work is to transform clinically collected image data into useful medical information to benefit healthcare at individual and societal levels.

The development and evaluation of BoneFinder, software to fully automatically outline skeletal structures in radiographs, has led to numerous national and international collaborations in the field of automated bone shape analyses applied to a range of skeletal structures such as the hips, knees and skull. Claudia's vision is to further develop the BoneFinder technology and to promote its use across applications in automated bone shape analyses, to ultimately benefit patients via methods for early diagnosis and improved management of disease.

Social responsibility

Claudia is a STEM Ambassador and regularly participates in public engagement activities such as running stands at science and technology fairs or going into schools to give talks to children about studying and careers in science.

Expertise related to UN Sustainable Development Goals

In 2015, UN member states agreed to 17 global Sustainable Development Goals (SDGs) to end poverty, protect the planet and ensure prosperity for all. This person’s work contributes towards the following SDG(s):

  • SDG 3 - Good Health and Well-being

Research Beacons, Institutes and Platforms

  • Digital Futures
  • Institute for Data Science and AI
  • Christabel Pankhurst Institute


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Collaborations and top research areas from the last five years

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