Most of the techniques presented in are applied in the 3D object space, such as transfer function design, rendering volumetric data combined with semi-transparent polygonal meshes with depth peeling, and mesh-based volume editing. In, we focused on customizing a volume renderer for confocal microscopy data visualization in neurobiology research. The rest of this paper is organized as follows: Section 2 discusses related work Section 3 looks at the volume renderer within FluoRender and discusses how we ensure rendering precision Section 4 presents the 2D image space methods that we choose to integrate into FluoRender for confocal data visualization enhancement Section 5 discusses certain implementation details of the system Section 6 demonstrates the improvements by case studies we then conclude in Section 7.Īs stated in the introduction, the work presented in this paper is a continuation of our previous development of FluoRender. To enhance surface details and depth perception, we use 2D compositing to combine a shading and/or a shadow layer with MIP rendering. We improve 2D composting for multiple channels by the introduction of groups. For easier brightness/contrast adjustments and detail enhancement, we use 2D tone-mapping operators, including gamma, luminance and scale-space equalization.
The contributions of this paper are methods and techniques that can easily be used for detail enhancement and integrated into FluoRender. The retouching work with tools such as Photoshop is usually fraught with frustrations, because the commonly used image file formats for data exchange between the visualization tools and image processing packages lack the precision needed for further adjustment, and these packages are designed for photography rather than confocal data visualization. However, users of FluoRender still relied on image processing packages and attempted to enhance details from their retouching work. We have convinced many that DVR can bring out details even better with properly adjusted volume transfer function settings, and will also correctly render the spatial relationship of confocal data. The familiarity with results from MIP rather than DVR usually makes biologists regard MIP advantageous at rendering sharp details, and this is more common with neurobiologists working with confocal microscopy data, which have an abundance of detail. They also have been using tools such as Photoshop with volumetric data visualization results including those from Maximum Intensity Projection (MIP) and Direct Volume Rendering (DVR).
We noticed that most biologists working with microscopy data are actually experts on image processing packages such as Photoshop, which are used for a variety of tasks including combining images, adjusting brightness and contrast, adding annotations, etc. One problem that we started looking at were the features presented in 2D image processing packages, however commonly missing from volumetric visualization tools. The user group of FluoRender has expanded beyond our collaborating neurobiologists, and brought new challenges and problems that we have overlooked in our initial work. Since its initial release, we continued the development of FluoRender with an emphasis on detail enhancement. A preliminary comparison of an early version of FluoRender with other visualization tools commonly used by neurobiologists has shown its advantage for visualizing finely detailed biological data. It has a specially designed volume transfer function with suitable parameters for adjusting and fine-tuning visualization results of confocal volumes it incorporates three render modes for combining and mixing of multiple confocal channels and it supports rendering semi-transparent polygonal mesh together with volume data, for better definition of important biological boundaries. FluoRender is such an interactive visualization tool that we developed along with our neurobiologist collaborators. In order to faithfully reconstruct the 3D structural relationships and enhance the fine details from confocal volumes, specialized visualization tools are always demanded by neurobiologists, and biologists in general. The data acquired from confocal microscopy are abundant with finely detailed biological structures resulting fromfluorescent staining. In neurobiology research, laser scanning confocal microscopy, which is capable of capturing 3D volumes and 4D time sequences of biological samples, is an essential tool for neurobiologists to study the structures of and structural differences between samples.