Current Approaches for Image Fusion of Histological Data with Computed Tomography and Magnetic Resonance Imaging

Figure 5

Exemplary workflow of a feature-based approach by Chicherova et al. [20] based on data originating from extracted human jawbones [29]. First, SURF-feature points (blue dots) were detected in all 700 planes of the CT scan and the histological image (left). These descriptors were then compared in a higher-dimensional space (middle). Matching descriptors of both modalities form a plane that was used as a basis to estimate the position of the histological section in the CT volume (right). The plane was then further optimized by utilizing RANSAC (right). Reprinted by permission from Springer Nature customer service center GmbH: patch-based techniques in medical imaging. Patch-MI 2017. Lecture notes in Computer Science, vol 10530, Histology to μCT data matching using landmarks and a density-biased RANSAC, Chicherova, N., Fundana, K., Müller, B., Cattin, P.C., Copyright© 2014 springer international publishing Switzerland.