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A Novel Mouse Segmentation Method Based on Dynamic Contrast Enhanced Micro-CT Images
- Source :
- PLoS ONE, Vol 12, Iss 1, p e0169424 (2017), PLoS ONE
- Publication Year :
- 2017
- Publisher :
- Public Library of Science (PLoS), 2017.
-
Abstract
- With the development of hybrid imaging scanners, micro-CT is widely used in locating abnormalities, studying drug metabolism, and providing structural priors to aid image reconstruction in functional imaging. Due to the low contrast of soft tissues, segmentation of soft tissue organs from mouse micro-CT images is a challenging problem. In this paper, we propose a mouse segmentation scheme based on dynamic contrast enhanced micro-CT images. With a homemade fast scanning micro-CT scanner, dynamic contrast enhanced images were acquired before and after injection of non-ionic iodinated contrast agents (iohexol). Then the feature vector of each voxel was extracted from the signal intensities at different time points. Based on these features, the heart, liver, spleen, lung, and kidney could be classified into different categories and extracted from separate categories by morphological processing. The bone structure was segmented using a thresholding method. Our method was validated on seven BALB/c mice using two different classifiers: a support vector machine classifier with a radial basis function kernel and a random forest classifier. The results were compared to manual segmentation, and the performance was assessed using the Dice similarity coefficient, false positive ratio, and false negative ratio. The results showed high accuracy with the Dice similarity coefficient ranging from 0.709 ± 0.078 for the spleen to 0.929 ± 0.006 for the kidney.
- Subjects :
- Support Vector Machine
Computer science
Physiology
Respiratory System
Contrast Media
lcsh:Medicine
computer.software_genre
030218 nuclear medicine & medical imaging
Diagnostic Radiology
Machine Learning
Mice
0302 clinical medicine
Voxel
Immune Physiology
Image Processing, Computer-Assisted
Medicine and Health Sciences
Segmentation
lcsh:Science
Tomography
Mammals
Multidisciplinary
Radiology and Imaging
Heart
Anatomy
Thresholding
Radiographic Image Enhancement
030220 oncology & carcinogenesis
Radial basis function kernel
Vertebrates
Female
Research Article
Computer and Information Sciences
Imaging Techniques
Feature vector
Image processing
Neuroimaging
Iterative reconstruction
Research and Analysis Methods
Rodents
03 medical and health sciences
Artificial Intelligence
Diagnostic Medicine
Support Vector Machines
Animals
business.industry
lcsh:R
Organisms
Reproducibility of Results
Biology and Life Sciences
Pattern recognition
Kidneys
X-Ray Microtomography
Renal System
Support vector machine
Amniotes
Cardiovascular Anatomy
Cognitive Science
lcsh:Q
Artificial intelligence
Lungs
business
computer
Tomography, Spiral Computed
Spleen
Positron Emission Tomography
Neuroscience
Subjects
Details
- Language :
- English
- ISSN :
- 19326203
- Volume :
- 12
- Issue :
- 1
- Database :
- OpenAIRE
- Journal :
- PLoS ONE
- Accession number :
- edsair.doi.dedup.....e980a2084000dce6986af9b99656618f