Digital pathology consists of acquisition, management, sharing, analysing and interpretation of pathology information generated from digitized specimen slides. The digital slides are created when glass slides containing tissue sections are captured with a scanning device, to present a high-resolution digital image on a computer screen. The great advantages of digital image analysis system are that they offer reproducible quantitative data compared to conventional methods and reduce the inter-observer and intra-observer variability.
Here at the Comparative Experimental Pathology (CEP), we have integrated two commercially available systems (Leica Biosystems and Definiens) and an open-source tool, Qupath into our workflow. Having multiple image analysis solutions enables us to analyze a wide range of image formats ranging from .SVS to .CZI. Our image analysis programs can handle images from Hematoxylin-Eosin (HE), immunohistochemistry (IHC) or immunofluorescence (IF) staining on whole slide images (WSI) or tissue microarray (TMA). We can also share the digital slides over networks using specialized pathology software application such as eSlide Manager (Leica Biosystems). This virtual sharing allows us to collaborate with our project partners. Last but not least, the artificial intelligence-derived programs that we use are faster than manual estimation proving our digital platform as a highly efficient service to our collaborators.
Over the past years we were and still are partners in several multidisciplinary teams, which aim to integrate the digital pathology in the routine diagnostic workflow (e.g. “Entscheiderfabrik”.
Moreover, to improve “machine learning” and “deep learning” approaches especially in ways of usability (e.g. IPN2, funded by the “Bayerische Forschungsstiftung” (Bavarian Research Foundation)).
Responsible for Digital Pathology projects:
Dr. Rim Sabrina Jahan Sarker (Email: Sabrina.firstname.lastname@example.org)