The purpose of this paper is to present a survey of recent publications concerning visualization of medical images. These techniques are described in three profiles: segmentation and classification of 3D medical images

data integration of multimodality images

and rendering of volume data. The three catalogs of methods are classified and several specific examples of each class of algorithm are described. Many researchers are dealing with the problem of non invasive diagnosis. One way of doing this are the imaging techniques used in almost every clinical environment

e.g. Ultrasonography

X ray Computed Tomography(CT)

Magnetic Resonance Imaging(MRI)

fMRI

Positron Emission Tomography(PET)

Single Photon Emission Tomography(SPET)

ect. Segmentation aims at the location of segments of interest in the image and thus the partitioning of the image. The purpose of data integration is to combine image information from multiple modalities/protocols. Besides rendering

accurate and automatic segmentation and image registration/fusion techniques are both key problems in medical visualization. The visualization of multimodality images is the most challenging and promising direction in the field of three dimensional medical image visualization.