Three-dimensional reconstruction of human spinal cord based on histological serial sections

BACKGROUND： It is not possible to reconstruct the inner structure of the spinal cord, such as gray matter and spinal tracts, from the Visual Human Project database or CT and MRI databases, due to low image resolution and contrast in macrosection images. OBJECTIVE： To explore a semi-automatic computerized three-dimensional （3D） reconstruction of human spinal cord based on histological serial sections, in order to solve issues such as low contrast. DESIGN, TIME AND SETTING： An experimental study combining serial section techniques and 3D reconstruction, performed in the laboratory of Human Anatomy and Histoembryology at the Medical School of Nantong University during January to April 2008. SETTING： Department of Anatomy, Institute of Neurobiology, Jiangsu Province Key Laboratory of Neural Regeneration, Laboratory of Image Engineering. MATERIALS： A human lumbar spinal cord segment from fresh autopsy material of an adult male. METHODS： After 4% paraformaldehyde fixation for three days, serial sections of the lumbar spinal cord were cut on a Leica cryostat and mounted on slides in sequence, with eight sections aligned separately on each slide. All sections were stained with Luxol Fast Blue to reveal myelin sheaths. After gradient dehydration and clearing, the stained slides were coverslipped. Sections were observed and images recorded under a light microscope using a digital camera. Six images were acquired at x25 magnification and automatically stitched into a complete section image. After all serial images were obtained, 96 complete serial images of the human lumbar cord segment were automatically processed with ＂Curves＂, ＂Autocontrast＂, ＂Gray scale 8 bit＂, ＂Invert＂, ＂Image resize to 50%＂ steps using Photoshop 7.0 software. All images were added in order into 3D-DOCTOR 4.0 software as a stack, where serial images were automatically realigned with neighboring images and semi-automatically segmented for white matter and gray matter. Finally, simple surface and volume reconstruction were completed on a personal computer. The reconstructed human lumbar spinal cord segment was interactively observed, cut, and measured. MAIN OUTCOME MEASURES： The reconstructed human lumbar spinal cord segment. RESULTS： Compared with serial images obtained from other image modalities, such as CT, MRI, and macrosections from The Visual Human Project database, the Luxol Fast Blue stained histological serial section images exhibited higher resolution and contrast between gray and white matter. Image processing and 3D reconstruction steps were semi-automatically performed with related software. The 3D reconstructed human lumbar cord segment were observed, cut, and measured on a PC. CONCLUSION： A semi-automatically computerized method, based on histological serial sections, is an effective way to 3D-reconstruct the human spinal cord.

Automated Silicon-Substrate Ultra-Microtome for Automating the Collection of Brain Sections in Array Tomography

Understanding the structure and working principle of brain neural networks requires three-dimensional reconstruction of brain tissue samples using array tomography method.In order to improve the reconstruction performance,the sequence of brain sections should be collected with silicon wafers for subsequent electron microscopic imaging.However,the current collection of brain sections based on silicon substrate involve mainly manual collection,which requires the involvement of automation techniques to increase collection efficiency.This paper presents the design of an automatic collection device for brain sections.First,a novel mechanism based on circular silicon substrates is proposed for collection of brain sections;second,an automatic collection system based on microscopic object detection and feedback control strategy is proposed.Experimental results verify the function of the proposed collection device.Three objects(brain section,left baffle,right baffle)can be detected from microscopic images by the proposed detection method.Collection efficiency can be further improved with position feedback of brain sections well.It has been experimentally verified that the proposed device can well fulfill the task of automatic collection of brain sections.With the help of the proposed automatic collection device,human operators can be partially liberated from the tedious manual collection process and collection efficiency can be improved.