Abstract
Image resolution in 4D-CT is a crucial bottleneck that needs to be overcome for improved dose planning in radiotherapy for lung cancer. In this paper, we propose a novel patch-based algorithm to enhance the image quality of 4D-CT data. Our premise is that anatomical information missing in one phase can be recovered from complementary information embedded in other phases. We employ a patch-based mechanism to propagate information across phases for reconstruction of intermediate slices in the axial direction, where resolution is normally the lowest. Specifically, structurally-matching and spatially-nearby patches are combined for reconstruction of each patch. For greater sensitivity to anatomical nuances, we further employ a quad-tree technique to adaptively partition each slice of the image in each phase for more fine-grained refinement. Our evaluation based on a public 4D-CT lung data indicates that our algorithm gives very promising results with significantly enhanced image structures.
| Original language | English |
|---|---|
| Title of host publication | Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention |
| Pages | 214-222 |
| Number of pages | 9 |
| Volume | 15 |
| Edition | Pt 1 |
| Publication status | Published - 2012 Dec 1 |
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ASJC Scopus subject areas
- Medicine(all)
Cite this
Non-local means resolution enhancement of lung 4D-CT data. / Zhang, Y.; Wu, Guorong; Yap, Pew Thian; Feng, Qianjin; Lian, Jun; Chen, Wufan; Shen, Dinggang.
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention. Vol. 15 Pt 1. ed. 2012. p. 214-222.Research output: Chapter in Book/Report/Conference proceeding › Chapter
}
TY - CHAP
T1 - Non-local means resolution enhancement of lung 4D-CT data.
AU - Zhang, Y.
AU - Wu, Guorong
AU - Yap, Pew Thian
AU - Feng, Qianjin
AU - Lian, Jun
AU - Chen, Wufan
AU - Shen, Dinggang
PY - 2012/12/1
Y1 - 2012/12/1
N2 - Image resolution in 4D-CT is a crucial bottleneck that needs to be overcome for improved dose planning in radiotherapy for lung cancer. In this paper, we propose a novel patch-based algorithm to enhance the image quality of 4D-CT data. Our premise is that anatomical information missing in one phase can be recovered from complementary information embedded in other phases. We employ a patch-based mechanism to propagate information across phases for reconstruction of intermediate slices in the axial direction, where resolution is normally the lowest. Specifically, structurally-matching and spatially-nearby patches are combined for reconstruction of each patch. For greater sensitivity to anatomical nuances, we further employ a quad-tree technique to adaptively partition each slice of the image in each phase for more fine-grained refinement. Our evaluation based on a public 4D-CT lung data indicates that our algorithm gives very promising results with significantly enhanced image structures.
AB - Image resolution in 4D-CT is a crucial bottleneck that needs to be overcome for improved dose planning in radiotherapy for lung cancer. In this paper, we propose a novel patch-based algorithm to enhance the image quality of 4D-CT data. Our premise is that anatomical information missing in one phase can be recovered from complementary information embedded in other phases. We employ a patch-based mechanism to propagate information across phases for reconstruction of intermediate slices in the axial direction, where resolution is normally the lowest. Specifically, structurally-matching and spatially-nearby patches are combined for reconstruction of each patch. For greater sensitivity to anatomical nuances, we further employ a quad-tree technique to adaptively partition each slice of the image in each phase for more fine-grained refinement. Our evaluation based on a public 4D-CT lung data indicates that our algorithm gives very promising results with significantly enhanced image structures.
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UR - http://www.scopus.com/inward/citedby.url?scp=84872526051&partnerID=8YFLogxK
M3 - Chapter
C2 - 23285554
AN - SCOPUS:84872526051
VL - 15
SP - 214
EP - 222
BT - Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
ER -