In this article we present a survey of medical image processing with the stress on applications of image generation and pattern recognition / understanding to computer aided diagnosis (CAD) and surgery (CAS). First, topics and fields of research in medical image processing are summarized. Second the importance of the 3D image processing and the use of virtualized human body (VHB) is pointed out. Thirdly the visualization and the observation methods of the VHB are introduced. In the forth section the virtualized endoscope system is presented from the viewpoint of the observation of the VHB with the moving viewpoints. The fifth topic is the use of VHB with deformation such as the simulation of surgical operation, intra-operative aids and image overlay. In the seventh section several topics on image processing methodologies are introduced including model generation, registration, segmentation, rendering and the use of knowledge processing.

In this paper we propose a new medical image processing system called Virtualized Endoscope System (VES)", which can examine the inside of a virtualized human body. The virtualized human body is a 3-D digital image which is taken by such as X-ray CT scanner or MRI scanner. VES consists of three modules; (1) imaging, (2) segmentation and reconstruction and (3) interactive operation. The interactive operation module has following thee major functions; (a) display of, (b) measurement from, and (c) manipulation to the virtualized human body. The user of the system can observe freely both the inside and the outside of a target organ from any point and any direction freely, and can perform necessary measurement interactively concerning angle and length at any time during observation. VES enables to observe repeatedly an area where the real endoscope can not enter without pain from any direction which the real endoscope can not. We applied this system to real 3-D X-ray CT images and obtained good result.

In this paper, we present new algorithms to calculate the reverse distance transformation and to extract the skeleton based upon the Euclidean metric for an arbitrary binary picture. The presented algorithms are applicable to an arbitrary picture in all of n-dimensional spaces (n2) and a digitized picture sampled with the different sampling interval in each coordinate axis. The reconstruction algorithm presented in this paper is resolved to serial one-dimensional operations and efficiently executed by general purpose computer. The memory requirement is very small including only one picture array and single one-dimensional work space array for n-dimensional pictures. We introduce two different definitions of skeletons, both of them allow us to reconstruct the original binary picture exactly, and present algorithms to extract those skeltons from the result of the squared Euclidean distance transformation.

This letter briefly introduces the software package SLIP (Subroutine Library for Image Processing) which is a collection of subroutine programs for image processing and pattern recognition. At present, about 340 subroutines of SLIP are available at the Nagoya University Computation Center.

This letter presents the connectivity number of 1-voxels in a 3-D digitized binary picture, and gives the necessary and sufficient condition that a 1-voxel in a 3-D picture is deletable. A shrinking algorithm for a 3-D object is suggested by using these results.

This letter presents definitions of connectivity among volume cells of a three-dimensional (3-D) digitized binary picture, and an explicit formula to calculate the Euler number of a 3-D object in a given 3-D picture.