Co-registration of Histological, Optical and MR Data of the Human Brain
MICCAI '02 Proceedings of the 5th International Conference on Medical Image Computing and Computer-Assisted Intervention-Part I
Image Registration of Sectioned Brains
International Journal of Computer Vision
Minimizing Nonsubmodular Functions with Graph Cuts-A Review
IEEE Transactions on Pattern Analysis and Machine Intelligence
Smooth 3-D Reconstruction for 2-D Histological Images
IPMI '09 Proceedings of the 21st International Conference on Information Processing in Medical Imaging
A Database and Evaluation Methodology for Optical Flow
International Journal of Computer Vision
3D mouse brain reconstruction from histology using a coarse-to-fine approach
WBIR'06 Proceedings of the Third international conference on Biomedical Image Registration
| Hi-index | 0.00 |
The reconstruction of histology sections into a 3-D volume receives increased attention due to its various applications in modern medical image analysis. To guarantee a geometrically coherent reconstruction, we propose a new way to register histological sections simultaneously to previously acquired reference images and to neighboring slices in the stack. To this end, we formulate two potential functions and associate them to the same Markov random field through which we can efficiently find an optimal solution. Due to our simultaneous formulation and the absence of any segmentation step during the reconstruction we can dramatically reduce error propagation effects. This is illustrated by experiments on carefully created synthetic as well as real data sets.