Abstract
Brain tissue segmentation of neonate MR images is a challenging task in study of early brain development, due to low signal contrast among brain tissues and high intensity variability especially in white matter. Among various brain tissue segmentation algorithms, the atlas-based segmentation techniques can potentially produce reasonable segmentation results on neonatal brain images. However, their performance on the population-based atlas is still limited due to the high variability of brain structures across different individuals. Moreover, it may be impossible to generate a reasonable probabilistic atlas for neonates without tissue segmentation samples. To overcome these limitations, we present a neonatal brain tissue segmentation method by taking advantage of the longitudinal data available in our study to establish a subject-specific probabilistic atlas. In particular, tissue segmentation of the neonatal brain is formulated as two iterative steps of bias correction and probabilistic atlas based tissue segmentation, along with the guidance of brain tissue segmentation resulted from the later time images of the same subject which serve as a subject-specific probabilistic atlas. The proposed method has been evaluated qualitatively through visual inspection and quantitatively by comparing with manual delineation results. Experimental results show that the utilization of a subject-specific probabilistic atlas can substantially improve tissue segmentation of neonatal brain images.
| Original language | English |
|---|---|
| Title of host publication | Progress in Biomedical Optics and Imaging - Proceedings of SPIE |
| Volume | 7259 |
| DOIs | |
| Publication status | Published - 2009 Dec 15 |
| Externally published | Yes |
| Event | Medical Imaging 2009 - Image Processing - Lake Buena Vista, FL, United States Duration: 2009 Feb 8 → 2009 Feb 10 |
Other
| Other | Medical Imaging 2009 - Image Processing |
|---|---|
| Country | United States |
| City | Lake Buena Vista, FL |
| Period | 09/2/8 → 09/2/10 |
Fingerprint
Keywords
- Neonate
- Probabilistic atlas
- Subject-specific atlas
- Tissue segmentation
ASJC Scopus subject areas
- Atomic and Molecular Physics, and Optics
- Electronic, Optical and Magnetic Materials
- Biomaterials
- Radiology Nuclear Medicine and imaging
Cite this
Brain tissue segmentation of neonatal MR images using a longitudinal subject-specific probabilistic atlas. / Shi, Feng; Fan, Yong; Tang, Songyuan; Gilmore, John; Lin, Weili; Shen, Dinggang.
Progress in Biomedical Optics and Imaging - Proceedings of SPIE. Vol. 7259 2009. 725942.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Brain tissue segmentation of neonatal MR images using a longitudinal subject-specific probabilistic atlas
AU - Shi, Feng
AU - Fan, Yong
AU - Tang, Songyuan
AU - Gilmore, John
AU - Lin, Weili
AU - Shen, Dinggang
PY - 2009/12/15
Y1 - 2009/12/15
N2 - Brain tissue segmentation of neonate MR images is a challenging task in study of early brain development, due to low signal contrast among brain tissues and high intensity variability especially in white matter. Among various brain tissue segmentation algorithms, the atlas-based segmentation techniques can potentially produce reasonable segmentation results on neonatal brain images. However, their performance on the population-based atlas is still limited due to the high variability of brain structures across different individuals. Moreover, it may be impossible to generate a reasonable probabilistic atlas for neonates without tissue segmentation samples. To overcome these limitations, we present a neonatal brain tissue segmentation method by taking advantage of the longitudinal data available in our study to establish a subject-specific probabilistic atlas. In particular, tissue segmentation of the neonatal brain is formulated as two iterative steps of bias correction and probabilistic atlas based tissue segmentation, along with the guidance of brain tissue segmentation resulted from the later time images of the same subject which serve as a subject-specific probabilistic atlas. The proposed method has been evaluated qualitatively through visual inspection and quantitatively by comparing with manual delineation results. Experimental results show that the utilization of a subject-specific probabilistic atlas can substantially improve tissue segmentation of neonatal brain images.
AB - Brain tissue segmentation of neonate MR images is a challenging task in study of early brain development, due to low signal contrast among brain tissues and high intensity variability especially in white matter. Among various brain tissue segmentation algorithms, the atlas-based segmentation techniques can potentially produce reasonable segmentation results on neonatal brain images. However, their performance on the population-based atlas is still limited due to the high variability of brain structures across different individuals. Moreover, it may be impossible to generate a reasonable probabilistic atlas for neonates without tissue segmentation samples. To overcome these limitations, we present a neonatal brain tissue segmentation method by taking advantage of the longitudinal data available in our study to establish a subject-specific probabilistic atlas. In particular, tissue segmentation of the neonatal brain is formulated as two iterative steps of bias correction and probabilistic atlas based tissue segmentation, along with the guidance of brain tissue segmentation resulted from the later time images of the same subject which serve as a subject-specific probabilistic atlas. The proposed method has been evaluated qualitatively through visual inspection and quantitatively by comparing with manual delineation results. Experimental results show that the utilization of a subject-specific probabilistic atlas can substantially improve tissue segmentation of neonatal brain images.
KW - Neonate
KW - Probabilistic atlas
KW - Subject-specific atlas
KW - Tissue segmentation
UR - http://www.scopus.com/inward/record.url?scp=71649103501&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=71649103501&partnerID=8YFLogxK
U2 - 10.1117/12.811610
DO - 10.1117/12.811610
M3 - Conference contribution
AN - SCOPUS:71649103501
SN - 9780819475107
VL - 7259
BT - Progress in Biomedical Optics and Imaging - Proceedings of SPIE
ER -