title: Supercomputer algorithms for efficient linear octree encoding of three-dimensional brain images.
abstract: We designed and implemented algorithms for three-dimensional (3-D) reconstruction of brain images from serial sections using two important supercomputer architectures, vector and parallel. These architectures were represented by the Cray YMP and Connection Machine CM-2, respectively. The programs operated on linear octree representations of the brain data sets, and achieved 500-800 times acceleration when compared with a conventional laboratory workstation. As the need for higher resolution data sets increases, supercomputer algorithms may offer a means of performing 3-D reconstruction well above current experimental limits.
authors.affiliation: Department of Diagnostic Imaging, Yale New Haven Hospital, New Haven, CT 06504, USA.
authors.forename: S B
authors.initials: SB
authors.lastname: Berger
authors.forename: D J
authors.initials: DJ
authors.lastname: Reis
mesh_terms: D000465:Algorithms; D000818:Animals; D001921:Brain / Q000033:anatomy & histology*; D003199:Computer Systems; D003952:Diagnostic Imaging; D007089:Image Enhancement; D007091:Image Processing, Computer-Assisted; D007256:Information Systems; D008297:Male; D008961:Models, Structural; D016571:Neural Networks, Computer; D011856:Radiographic Image Enhancement; D012815:Signal Processing, Computer-Assisted; D012986:Software Validation; D013997:Time Factors; D014057:Tomography, X-Ray Computed