High resolution three dimensional talairach labels for human brain mapping using shape-based interpolation

Since the 1810 cranioscopy claims of F.J.Gall, human brain mapping has evolved into a challenging but fascinating scientific endeavor. The works of Jean Talairach in stereotaxic neurosurgery has revolutionized the use of brain atlases to identify the spatial locations of brain activations derived from functional images. The availability of digital print atlases, standardization of Talairach coordinates as means of reporting activation spots and the availability of Talairach daemon has led to the proliferation of publications in human brain mapping. However, the VOTL database used in the Talairach daemon employs nearest-neighbor interpolation of the sparse and unevenly spaced Talairach atlas. This exacerbates the already existing errors in brain mapping. This paper introduces the use of a shape based interpolation algorithm to derive a high resolution three dimensional Talairach Atlas. It uses a feature-guided approach for shape-based interpolation of porous and tortuous binary objects. The feature points are derived from the boundaries of the candidate sources and matched non-linearly using a robust outlier rejecting, non-linear point matching algorithm based on thin plate splines. The proposed scheme correctly handles objects with holes, large offsets and drastic invagination and significantly enhances the sparse Talairach Atlas. A similar approach applied to Schalten-brand and Wahren atlas would add appreciable value to functional neurosurgery.