Resolution enhancement of lung 4D-CT data using multiscale interphase iterative nonlocal means

Journal Article · Wed May 15 00:00:00 EDT 2013 · Medical Physics

DOI:https://doi.org/10.1118/1.4802747· OSTI ID:22130628

Yu, Zhang ^[1]; Yap, Pew-Thian; Guorong, Wu ^[2]; Qianjin, Feng; Wufan, Chen ^[3]; Jun, Lian ^[4]; Dinggang, Shen ^[2]

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1. School of Biomedical Engineering, Southern Medical University, Guangzhou 510515, China and Department of Radiology and BRIC, University of North Carolina, Chapel Hill, North Carolina 27599 (United States)
2. Department of Radiology and BRIC, University of North Carolina, Chapel Hill, North Carolina 27599 (United States)
3. School of Biomedical Engineering, Southern Medical University, Guangzhou 510515 (China)
4. Department of Radiation Oncology, University of North Carolina, Chapel Hill, North Carolina 27599 (United States)

Purpose: Four-dimensional computer tomography (4D-CT) has been widely used in lung cancer radiotherapy due to its capability in providing important tumor motion information. However, the prolonged scanning duration required by 4D-CT causes considerable increase in radiation dose. To minimize the radiation-related health risk, radiation dose is often reduced at the expense of interslice spatial resolution. However, inadequate resolution in 4D-CT causes artifacts and increases uncertainty in tumor localization, which eventually results in extra damages of healthy tissues during radiotherapy. In this paper, the authors propose a novel postprocessing algorithm to enhance the resolution of lung 4D-CT data. Methods: The authors' premise is that anatomical information missing in one phase can be recovered from the complementary information embedded in other phases. The authors employ a patch-based mechanism to propagate information across phases for the reconstruction of intermediate slices in the longitudinal direction, where resolution is normally the lowest. Specifically, the structurally matching and spatially nearby patches are combined for reconstruction of each patch. For greater sensitivity to anatomical details, the authors employ a quad-tree technique to adaptively partition the image for more fine-grained refinement. The authors further devise an iterative strategy for significant enhancement of anatomical details. Results: The authors evaluated their algorithm using a publicly available lung data that consist of 10 4D-CT cases. The authors' algorithm gives very promising results with significantly enhanced image structures and much less artifacts. Quantitative analysis shows that the authors' algorithm increases peak signal-to-noise ratio by 3-4 dB and the structural similarity index by 3%-5% when compared with the standard interpolation-based algorithms. Conclusions: The authors have developed a new algorithm to improve the resolution of 4D-CT. It outperforms the conventional interpolation-based approaches by producing images with the markedly improved structural clarity and greatly reduced artifacts.

• OSTI ID: 22130628
• Journal Information: Medical Physics, Vol. 40, Issue 5; Other Information: (c) 2013 American Association of Physicists in Medicine; Country of input: International Atomic Energy Agency (IAEA); ISSN 0094-2405
• Country of Publication: United States
• Language: English

Related Subjects

62 RADIOLOGY AND NUCLEAR MEDICINE
61 RADIATION PROTECTION AND DOSIMETRY
60 APPLIED LIFE SCIENCES
71 CLASSICAL AND QUANTUM MECHANICS
GENERAL PHYSICS
ALGORITHMS
COMPUTERIZED TOMOGRAPHY
DOSIMETRY
FOUR-DIMENSIONAL CALCULATIONS
HEALTH HAZARDS
IMAGE PROCESSING
IMAGES
INTERPOLATION
ITERATIVE METHODS
LUNGS
PEAKS
RADIATION DOSES
RADIOTHERAPY
SENSITIVITY
SIGNAL-TO-NOISE RATIO
SPATIAL RESOLUTION