Intensity Modulated Radiotherapy Target Volume Definition by Means of Wavelet Segmentation
This study aimed to develop an advance precision three-dimensional (3-D) image segmentation algorithm to enhance the blurred edges clearly and then introduce the result onto the intensity modulated radiotherapy (IMRT) for tumor target volume definition. This will achieve what physicians usually demand that tumor doses escalation characteristics of IMRT. A proposed algorithm flowchart designed for this precision 3-D treatment targeting was introduced in this paper. Different medical images were used to test the validity of the proposed method. The 3-D wavelet based targeting preprocessing segmentation allows physicians to improve the traditional treatments or IMRT much more accurately and effectively. This will play an important role in image-guided radiotherapy (IGRT) and many other medical applications in the future.
Keywordsintensity modulated radiotherapy target volume wavelet segmentation
Unable to display preview. Download preview PDF.
- 2.Intensity Modulated Radiation Therapy Collaborative Working Group (IMRTCWG). Intensity modulated radiotherapy: Current status and issues of interest. International Journal Radiation Oncology Biology Phys. 51, 880–914 (2001)Google Scholar
- 5.Chakraborty, A.: Feature and Module Integration for Image Segmentation. PhD thesis, Yale University, 89-185 (1996)Google Scholar
- 7.Ku, C.T., Hung, K.C., Liag, M.C.: Wavelet Operators for Multi-scale Edge and Corner Detection. Master thesis, Department of Electrical Engineering, I-Shou University, Taiwan, 4-65 (1998)Google Scholar
- 8.Leu, Y.S., Chou, C.J.: Wavelet Edge Detection on Region-based Image Segmentation. Master thesis, Department of Computer & Communication Engineering, National Kaohsiung First University of Science and Technology, Taiwan, 8-27 (2000)Google Scholar
- 11.Gonzalez, R.C., Woods, R.E.: Digital Image Processing, 2nd edn., pp. 349–405. Prentice-Hall, Englewood Cliffs (2002)Google Scholar
- 13.Russ, J.C.: The Image Processing Handbook, 3rd edn., pp. 23–138. CRC Press & IEEE Press (1999)Google Scholar
- 15.Gonzalez, R.C., Woods, R.E.: Digital Image Processing, 2nd edn., pp. 612–617. Prentice-Hall, Englewood Cliffs (2004)Google Scholar
- 16.Russ, J.C.: The Image Processing Handbook, 3rd edn. CRC Press & IEEE Press (1999)Google Scholar