Computational intelligent image analysis for assisting radiation oncologists' decision making in radiation treatment planning

Hidetaka Arimura, Taiki Magome, Genyu Kakiuchi, Jumpei Kuwazuru, Asumi Mizoguchi

Research output: Chapter in Book/Report/Conference proceedingChapter

Abstract

This chapter describes the computational image analysis for assisting radiation oncologists' decision making in radiation treatment planning for high precision radiation therapy. The radiation therapy consists of five steps, i.e., diagnosis, treatment planning, patient setup, treatment, and follow-up, in which computational intelligent image analysis and pattern recognition methods play important roles in improving the accuracy of radiation therapy and assisting radiation oncologists' or medical physicists' decision making. In particular, the treatment planning step is substantially important and indispensable, because the subsequent steps must be performed according to the treatment plan. This chapter introduces a number of studies on computational intelligent image analysis used for the computer-Aided decision making in radiation treatment planning. Moreover, the authors also explore computer-Aided treatment planning methods including automated beam arrangement based on similar cases, computerized contouring of lung tumor regions using a support vector machine (SVM) classifier, and a computerized method for determination of robust beam directions against patient setup errors in particle therapy.

Original languageEnglish
Title of host publicationComputational Intelligence in Biomedical Imaging
PublisherSpringer New York
Pages83-103
Number of pages21
Volume9781461472452
ISBN (Electronic)9781461472452
ISBN (Print)146147244X, 9781461472445
DOIs
Publication statusPublished - Jul 1 2014

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Image analysis
Decision making
Radiotherapy
Radiation
Planning
Patient treatment
Pattern recognition
Support vector machines
Tumors
Classifiers

All Science Journal Classification (ASJC) codes

  • Computer Science(all)

Cite this

Arimura, H., Magome, T., Kakiuchi, G., Kuwazuru, J., & Mizoguchi, A. (2014). Computational intelligent image analysis for assisting radiation oncologists' decision making in radiation treatment planning. In Computational Intelligence in Biomedical Imaging (Vol. 9781461472452, pp. 83-103). Springer New York. https://doi.org/10.1007/978-1-4614-7245-2_4

Computational intelligent image analysis for assisting radiation oncologists' decision making in radiation treatment planning. / Arimura, Hidetaka; Magome, Taiki; Kakiuchi, Genyu; Kuwazuru, Jumpei; Mizoguchi, Asumi.

Computational Intelligence in Biomedical Imaging. Vol. 9781461472452 Springer New York, 2014. p. 83-103.

Research output: Chapter in Book/Report/Conference proceedingChapter

Arimura, H, Magome, T, Kakiuchi, G, Kuwazuru, J & Mizoguchi, A 2014, Computational intelligent image analysis for assisting radiation oncologists' decision making in radiation treatment planning. in Computational Intelligence in Biomedical Imaging. vol. 9781461472452, Springer New York, pp. 83-103. https://doi.org/10.1007/978-1-4614-7245-2_4
Arimura H, Magome T, Kakiuchi G, Kuwazuru J, Mizoguchi A. Computational intelligent image analysis for assisting radiation oncologists' decision making in radiation treatment planning. In Computational Intelligence in Biomedical Imaging. Vol. 9781461472452. Springer New York. 2014. p. 83-103 https://doi.org/10.1007/978-1-4614-7245-2_4
Arimura, Hidetaka ; Magome, Taiki ; Kakiuchi, Genyu ; Kuwazuru, Jumpei ; Mizoguchi, Asumi. / Computational intelligent image analysis for assisting radiation oncologists' decision making in radiation treatment planning. Computational Intelligence in Biomedical Imaging. Vol. 9781461472452 Springer New York, 2014. pp. 83-103
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