Registration and segmentation in medical imaging

Rueckert D, Schnabel JA (2014)


Publication Type: Book chapter / Article in edited volumes

Publication year: 2014

Journal

Publisher: Springer Verlag

Edited Volumes: Registration and Recognition in Images and Videos

Series: Studies in Computational Intelligence

Book Volume: 532

Pages Range: 137-156

DOI: 10.1007/978-3-642-44907-9_7

Abstract

The analysis of medical images plays an increasingly important role in many clinical applications. Different imaging modalities often provide complementary anatomical information about the underlying tissues such as the X-ray attenuation coefficients from X-ray computed tomography (CT), and proton density or proton relaxation times from magnetic resonance (MR) imaging. The images allow clinicians to gather information about the size, shape and spatial relationship between anatomical structures and any pathology, if present. Other imaging modalities provide functional information such as the blood flow or glucose metabolism from positron emission tomography (PET) or single-photon emission tomography (SPECT), and permit clinicians to study the relationship between anatomy and physiology. Finally, histological images provide another important source of information which depicts structures at a microscopic level of resolution. © 2014 Springer-Verlag Berlin Heidelberg.

Involved external institutions

How to cite

APA:

Rueckert, D., & Schnabel, J.A. (2014). Registration and segmentation in medical imaging. In Registration and Recognition in Images and Videos. (pp. 137-156). Springer Verlag.

MLA:

Rueckert, Daniel, and Julia A. Schnabel. "Registration and segmentation in medical imaging." Registration and Recognition in Images and Videos. Springer Verlag, 2014. 137-156.

BibTeX: Download