IMPROMPTU: a system for automatic 3D medical image-analysis.

The utility of three-dimensional (3D) medical imaging is hampered by difficulties in extracting anatomical regions and making measurements in 3D images. Presently, a user is generally forced to use time-consuming, subjective, manual methods, such as slice tracing and region painting, to define regions of interest. Automatic image-analysis methods can ameliorate the difficulties of manual methods. This paper describes a graphical user interface (GUI) system for constructing automatic image-analysis processes for 3D medical-imaging applications. The system, referred to as IMPROMPTU, provides a user-friendly environment for prototyping, testing and executing complex image-analysis processes. IMPROMPTU can stand alone or it can interact with an existing graphics-based 3D medical image-analysis package (VIDA), giving a strong environment for 3D image-analysis, consisting of tools for visualization, manual interaction, and automatic processing. IMPROMPTU links to a large library of 1D, 2D, and 3D image-processing functions, referred to as VIPLIB, but a user can easily link in custom-made functions. 3D applications of the system are given for left-ventricular chamber, myocardial, and upper-airway extractions.

[1]  Eric A. Hoffman,et al.  Graphical user interface system for automatic 3-D medical image analysis , 1992, [1992] Proceedings Fifth Annual IEEE Symposium on Computer-Based Medical Systems.

[2]  William E. Higgins,et al.  A flexible implementation of maximum-homogeneity filtering for 2-D and 3-D images , 1991, IEEE Trans. Signal Process..

[3]  Eric A. Hoffman,et al.  A historical perspective of heart and lung 3D imaging , 1991 .

[4]  E A Hoffman,et al.  Multimodality imaging of the upper airway: MRI, MR spectroscopy, and ultrafast X-ray CT. , 1990, Progress in clinical and biological research.

[5]  P M Suratt,et al.  Sleep and respiration. , 1990, Journal of applied physiology.

[6]  G. Herman,et al.  3D Imaging In Medicine , 1991 .

[7]  U Tiede,et al.  3-D segmentation of MR images of the head for 3-D display. , 1990, IEEE transactions on medical imaging.

[8]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[9]  E L Ritman,et al.  LV chamber extraction from 3-D CT images--accuracy and precision. , 1992, Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society.

[10]  E L Ritman,et al.  Extraction of left-ventricular chamber from 3-D CT images of the heart. , 1990, IEEE transactions on medical imaging.

[11]  William E. Higgins,et al.  Interactive relaxation labeling for 3D cardiac image analysis , 1993, Electronic Imaging.

[12]  W E Higgins,et al.  Interactive morphological watershed analysis for 3D medical images. , 1993, Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society.

[13]  Eric A. Hoffman,et al.  VIDA: an environment for multidimensional image display and analysis , 1992, Electronic Imaging.

[14]  R A Robb,et al.  Interactive display and analysis of 3-D medical images. , 1989, IEEE transactions on medical imaging.

[15]  Martin R. Stytz,et al.  Three-dimensional medical imaging: algorithms and computer systems , 1991, CSUR.

[16]  Ross T. Whitaker,et al.  Direct visualization of volume data , 1992, IEEE Computer Graphics and Applications.

[17]  J.L. Coatrieux,et al.  Future trends in 3D medical imaging , 1990, IEEE Engineering in Medicine and Biology Magazine.

[18]  Takashi Matsuyama.  Expert systems for image processing: Knowledge-based composition of image analysis processes , 1989, Comput. Vis. Graph. Image Process..

[19]  Jean Serra,et al.  Image Analysis and Mathematical Morphology , 1983 .