Multimodal histological image registration using locally rigid transforms
2015 (English)In: Proc. Interactive Medical Image Computing Workshop, 2015Conference paper (Refereed)
Evaluating multimodal histological images is an important task within cancer diagnosis. Using aligned consecutive sections is still the most straight-forward approach for combining multimodal data.
To overcome the difficulties in aligning the sections, we present an interactive registration approach and show its usage for aligning TMA core images from consecutive sections stained for different biomarkers. In order to reduce distortion of local structures, a global deformable transform is approximated with locally more or less rigid transformations. This gives a trade-off between registration quality and distortion of local structures. The method divides the registration in an offline (global registration) and online step, where the local approximation is done in real-time within current field of view. This approach gives the viewer the ability to quickly adjust the rigidity from a deformable, well-aligned transformation to a rigid where structures "look right''.
Place, publisher, year, edition, pages
Medical Image Processing
Research subject Computerized Image Processing
IdentifiersURN: urn:nbn:se:uu:diva-267414OAI: oai:DiVA.org:uu-267414DiVA: diva2:873070
Interactive Medical Image Computing (IMIC) Workshop at MICCAI 2015, October 5–9, Munich, Germany