Object-oriented region-of-interest toolkit for workstations

Medical imaging workstations need capabilities for defining a Region Of Interest (ROI) within an image, so that it can be processed for visualization or quantitative measurements. The purpose of this work was to develop a generic, object-oriented toolkit which allows creation, modification, querying and traversal of an ROI. In the object-oriented design, an ROI class is defined with associated methods. An ROI object consists of a set of 3-D points represented using interval- end-points. The ROI toolkit has been developed using C++, in conjunction with patient browser and image object navigation (display) toolkits, to serve as the foundation for thoracic and neuro-radiology workstations. Because of the object-oriented design and generic representation of the ROI, this toolkit can easily facilitate standard and advanced image processing methods.

[1]  John C. Russ,et al.  The Image Processing Handbook , 2016, Microscopy and Microanalysis.

[2]  L. Hedlund,et al.  Two methods for isolating the lung area of a CT scan for density information. , 1982, Radiology.

[3]  Bjarne Stroustrup,et al.  The C++ programming language (2nd ed.) , 1991 .

[4]  E. Hoffman,et al.  Noninvasive quantitative imaging of shape and volume of lungs. , 1983, Journal of applied physiology: respiratory, environmental and exercise physiology.

[5]  W. Lorensen,et al.  Two algorithms for the three-dimensional reconstruction of tomograms. , 1988, Medical physics.

[6]  Milan Sonka,et al.  Image pre-processing , 1993 .

[7]  E J Breen,et al.  Dynamic arrays for fast, efficient, data manipulation during image analysis: a new software tool for exploratory data analysis. , 1992, Computer methods and programs in biomedicine.

[8]  Michael F. McNitt-Gray,et al.  Extensible knowledge-based architecture for segmenting CT data , 1998, Medical Imaging.

[9]  John C. Russ,et al.  The image processing handbook (3. ed.) , 1995 .

[10]  Jim Piper,et al.  Data structures for image processing in a C language and Unix environment , 1985, Pattern Recognit. Lett..

[11]  Hanan Samet,et al.  A Tutorial on Quadtree Research , 1984 .

[12]  Michael F. McNitt-Gray,et al.  Automated assessment of split lung functon in post-lung-transplant evaluation , 1998, Medical Imaging.

[13]  Brent Liu,et al.  Application development environment for advanced digital workstations , 1998, Medical Imaging.