Understanding Medical Images Based on Computational Anatomy Models

Shouhei Hanaoka, Naoki Kamiya, Yoshinobu Sato, Kensaku Mori, Hiroshi Fukuda, Yasuyuki Taki, Kazunori Sato, Kai Wu, Yoshitaka Masutani, Takeshi Hara, Chisako Muramatsu, Akinobu Shimizu, Mikio Matsuhiro, Yoshiki Kawata, Noboru Niki, Daisuke Fukuoka, Tomoko Matsubara, Hidenobu Suzuki, Ryo Haraguchi, Toshizo KatsudaTakayuki Kitasaka

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

2 Citations (Scopus)


This chapter presents examples of medical image understanding algorithms using computational anatomy models explained in Chap. 2. After the introductory in Sect. 3.1, Sect. 3.2 shows segmentation algorithms for vertebrae, ribs, and hip joints. Segmentation algorithms for skeletal muscle and detection algorithms for lymph nodes are explained in Sects. 3.3 and 3.4, respectively. Section 3.5 deals with algorithms for understanding organs/tissues in the head and neck regions and starts with computational neuroanatomy, followed by analysis and segmentation algorithms for white matter, brain CT, oral regions, fundus oculi, and retinal optical coherence tomography (OCT). Algorithms useful in the thorax, specifically for the lungs, tracheobronchial tree, vessels, and interlobar fissures from a thoracic CT volume, are presented in Sect. 3.6. Section 3.7 provides algorithms for breast ultrasound imaging, i.e., mammography and breastMRI. Cardiac imaging algorithms in an echocardiographic image sequence and MR images as well as coronary arteries in a CT volume are explained in Sect. 3.8. Section 3.9 deals with segmentation algorithms of abdominal organs, including the liver, pancreas, spleen, kidneys, gastrointestinal tract, and abdominal blood vessels, followed by anatomical labeling of segmented vessels.

Original languageEnglish
Title of host publicationComputational Anatomy Based on Whole Body Imaging
Subtitle of host publicationBasic Principles of Computer-Assisted Diagnosis and Therapy
PublisherSpringer Japan
Number of pages134
ISBN (Electronic)9784431559764
ISBN (Print)9784431559740
Publication statusPublished - 2017 Jun 14


  • Abdomen
  • CT
  • Fundus image
  • Head
  • MR
  • Neck
  • OCT
  • Segmentation
  • Thoracic
  • X-ray


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