From Individual to Population: Challenges in Medical Visualization - Scientific Visualization: Uncertainty, Multifield, Biomedical, and Scalable Visualization - page 250

1978 - Sunguroff and Greenberg:CTand3Dsurfaces for diagnosis and radiotherapy planning [64].
1983 - Vannier et al.: 3D surfaces from CT for planning of craniofacial surgery [71].
1986 - Hohne and Bernstein: Shading 3D Images from CT usinggray-level gradients [26].
1987 - Lorensen and Cline: Marching Cubes [49].
1988 - Levoy publishes Direct Volume Rendering paper in May [47], Drebin et al. in August [19].
Multi-modal volume rendering by Hohne et al. [27].
1993 - Altobelli et al.: Predictive simulation in surgical planning [1]. Gerig et al.: Vessel visualization [23].
1994 - Basser et al.: Diffusion Tensor Imaging [5].
1995 - Hong et al.: 3D Virtual Colonoscopy [28].
1996 - Behrens et al. et al.: Visualization of Dynamic Contrast-Enhanced MRI mammography data (time-varying) [7].
1998 - Basser et al.: DTI Tractography [4, 6].
2000 - Ebert and Rheingans - Medical Volume Illustration [20].
2001 - Tory et al.: Multi-timepoint MRI [69].
2003 - Kruger and Westermann: GPU raycasting [45].
2007 - Blaas et al.: Multi-Field Medical Visualization [9].
2008 - Wang et al.: LifeLines2 - multi-subject electronic health records [73].
2010 - Steenwijk et al.: Cohort studies - multi-subject imaging and metadata [63].
Fig. 23.1 Timeline with a subset of medical visualization papers showing the progression from
scalar volume datasets through time-dependent data to multi-field and finally multi-subject datasets.
This timeline is by no means complete, instead attempting to show a representative sample of papers
that represent various trends in the development of the field
the introduction of Marching Cubes and volume raycasting, volume visualization
became a core business of visualization and medical visualization for the years to
come.
Up to this point, research had focused on uni-modality data, primarily CT. How-
ever, already in 1988 the first multi-modal volume rendering paper was published
by Höhne et al., in which they demonstrated the registration and combined visual-
ization of CT and MRI. A great deal of work has been done since then on the theory
and applications of multi-modal volume visualization. The first notable example is
the work of Cai and Sakas in 1999 where they classified voxel-voxel multi-modal
volume rendering techniques according to the volume rendering pipeline stage where
they take place [ 13 ]. The three classes are image level, where two volume renderings
are combined pixel-by-pixel, accumulation level, where looked up samples along