Rigorous quantification methods of histological specimens have become a keystone in modern neuroscience such as investigations of neurogenesis, stem cell research, neurotransplantation, neurotoxicology, and the pathogenesis of neurodegenerative and neuropsychiatric diseases. Methods in current practice are not conducive to high-throughput studies because they are often manual and laborious to perform. There is a noticeable lack of computerized automated 3D quantitative histological analysis tools which can operate on large 3D image volumes. Furthermore, the widespread use of fluorescently labeled tissue sections imposes other limitations, particularly fading of fluorescent dyes, limited availability and tremendous costs of high-end confocal microscopes. We propose to develop a commercial system (Biolucida"""""""") to overcome this unsatisfactory situation. The core of Biolucida will be 3D virtual slides, which are digital representations (in X, Y and Z) of tissue specimens imaged through a microscope at the highest optical resolution. We will develop software for the acquisition, automated quantitative histological analysis, viewing, sharing and archiving of 3D virtual slides. As such, the use of Biolucida will fully surmount the aforementioned limitations. Consequently we expect that the launch of Biolucida will revolutionize the quantitative analysis of fluorescently labeled tissue sections in modern neuroscience. ? ? ?
| O'Connor, Nathan; Tappan, Susan; Glaser, Jacob (2014) How to prepare neuroanatomical image data. Curr Protoc Neurosci 69:1.21.1-14 |
