Multilayer image grid reconstruction technology: four-dimensional interactive image reconstruction of microsurgical neuroanatomic dissections.

Abstract

OBJECTIVE: Cadaveric dissection is the gold standard for training physicians in various surgical specialties. However, limitations in acquiring and storing sufficient cadaveric material, recent pressures in training opportunities, and progress in digital image technology have led to advances in virtual or artificial visual means to augment surgical training. For training neurosurgeons, the appearance of reality is still crucial for learning anatomic structures and procedures. We developed a four-dimensional (including time) multilayer digital image reconstruction technology (MIGRT) that allows users to manipulate a "volumetric" set of photographic image data from exquisite cadaveric intracranial dissections and to navigate through stages of neurosurgical procedures as the dissection progresses. METHODS: A robotic microscope with two digital cameras was used to capture dissection images, usually in stereoscopic mode. A grid space was created to define positions at which images are captured. Images were acquired from identical angles at the same grid coordinates but at different stages of various dissections. RESULTS: Image data are reconstructed according to the sequence of acquisition into a multilayer image grid system by the MIGRT software. The single interactive, four-dimensional montage is viewable a on common computer platform. CONCLUSION: MIGRT uniquely focuses on capturing anatomic content that preserves natural appearances, including procedure, texture, and color, which is far superior and preferable to images and a reconstructed image environment based on artificial or animated concepts. MIGRT shows time-dependent changes in procedures, provides depth perception by stereoscopy or unique sequential motion, and allows simultaneous interactivity at each step of the procedure.