| Speaker: |
Hideo Otsuna
Department of Neurobiology and Anatomy, University of Utah |
| Title: |
QBiC CDB Joint Seminar] New 3D/4D visualization/analysis methods for biological data |
| Summary : | Since 1990's, most biological data are digital; recently, more 3D/4D information is incorporated. However, it is time consuming to analyze these 3D/4D data manually. Furthermore, the limited skill on manual analysis of the imaging data by biologists restricts the output data quality or in some cases will lead to wrong conclusion given the limitation of visualization and presentation.
We have been developing computational methodologies of automatic image analysis since 2008. Our focus is mainly on biological image auto-analysis and automated processing by computational programming. I have been involving in multiple projects that fundamentally change the way of biological imaging processing: auto cell counting, automated distinguishing of cell shape and brightness measurement, 4D tissue drift canceling method, 4D brightness equalization method and large tissue 3D reconstruction method from paraffin slices.
We have also been developing 3D/4D visualization/segmentation software FluoRender. Recently, we have developed additional analysis functions in this software. In this session, I would like to discuss new visualization/analysis methods for various types of 3D/4D data using FluoRender and ImageJ. |
