| 1. |
Hidetaka Arimura, Image-Based Computer-Assisted Radiation Therapy Edited by Hidetaka Arimura, March 4, 2017, Springer, 2017.03, This book provides a comprehensive overview of the state-of-the-art computational intelligence research and technologies in computer-assisted radiation therapy based on image engineering. It also traces major technical advancements and research findings in the field of image-based computer-assisted radiation therapy.
In high-precision radiation therapies, novel approaches in image engineering including computer graphics, image processing, pattern recognition, and computational anatomy play important roles in improving the accuracy of radiation therapy and assisting decision making by radiation oncology professionals, such as radiation oncologists, radiation technologists, and medical physicists, in each phase of radiation therapy.
All the topics presented in this book broaden understanding of the modern medical technologies and systems for image-based computer-assisted radiation therapy. Therefore this volume will greatly benefit not only radiation oncologists and radiologists but also radiation technologists, professors in medical physics or engineering, and engineers involved in the development of products to utilize this advanced therapy.. |
| 2. |
Hidetaka Arimura, Taiki Magome, Genyu Kakiuchi, Jyunpei Kuwazuru, Asumi Mizoguchi, "Computational Intelligent Image Analysis for Assisting Radiation Oncologists’ Decision Making in Radiation Treatment Planning" in Computational Intelligence in Biomedical Imaging Edited by Kenji Suzuki (The University of Chicago) pp. 83-103, Springer Science+Business Media New York, Springer, 2013.12. |
| 3. |
Hidetaka Arimura, Chiaki Tokunaga, Yasuo Yamashita, Jyunpei Kuwazuru, "Magnetic Resonance Image Analysis for Brain CAD Systems with Machine Learning" in Machine Learning in Computer-Aided Diagnosis: Medical Imaging Intelligence and Analysis Edited by Kenji Suzuki (The University of Chicago) , IGI Global, pp. 258-296, IGI global, USA, 2012.01. |
