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Fundamental Theories and Techniques

Hidekata Hontani, Yasushi Hirano, Xiao Dong, Akinobu Shimizu, and Shohei Hanaoka

Abstract In this section, fundamental theories and techniques for understanding computational anatomy are described. First, the mathematical foundations of a signal processing and of statistics are discussed. Signal processing is the basis of the image processing required for extracting local image features that are useful for the identification of the organ regions in medical images, which is one of the most important tasks in CA. A knowledge of statistics is needed for understanding the statistical shape models (SSMs) of the organs and the registration of the models to given medical images, which is one of the most basic techniques used for the organ region identification. Second, model representations of the organs, e.g., point distribution models (PDMs), medial representations (m-reps), and nonuniform rational basis splines (NURBS), are described. Different models, e.g., a point distribution model (PDM), a medial representation (m-rep), or nonuniform rational basis splines (NURBS), can be employed for representing a target organ, and a region of a target organ in a given image can be identified by registering the

H. Hontani (H)

Department of Computer Science, Nagoya Institute of Technology, Gokiso, Showa-ku, Aichi 466-8555, Nagoya, Japan e-mail: This email address is being protected from spam bots, you need Javascript enabled to view it

Y. Hirano

Graduate School of Medicine, Yamaguchi University, 1677-1, Yoshida, Yamaguchi-shi,

735-8511, Yamaguchi, Japan e-mail: This email address is being protected from spam bots, you need Javascript enabled to view it

X. Dong

Faculty of Computer Science and Engineering, Southeast University, 2 Sipailou, Jiangsu, 210018, Nanjing, China

e-mail: This email address is being protected from spam bots, you need Javascript enabled to view it A. Shimizu

Institute of Engineering, Tokyo University of Agriculture and Technology, Naka-cho 2-24-16, Koanei, 184-0012, Tokyo, Japan e-mail: This email address is being protected from spam bots, you need Javascript enabled to view it

S. Hanaoka

Department of Radiology, The University of Tokyo Hospital, 7-3-1, Hongo, Bunkyo-ku, 113-8655, Tokyo, Japan e-mail: This email address is being protected from spam bots, you need Javascript enabled to view it

© Springer Japan KK 2017

H. Kobatake, Y. Masutani (eds.), Computational Anatomy Based on Whole Body Imaging, DOI 10.1007/978-4-431-55976-4_2

employed model to the image: Several techniques for the model registration are also discussed in this chapter. The performance of the organ region identification can change depending on the employed representation and on the employed registration technique. Finally, the difficulties posed by multiple organ registration and the handling of anatomical anomalies are considered.

Keywords Image segmentation • Model registration • Image registration • Statistical shape model • Point distribution model

 
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