Adaptive patch-based POCS approach for super resolution reconstruction of 4D-CT lung data

被引：10

作者：

Wang, Tingting ^{[1
]}

Cao, Lei ^{[1
]}

Yang, Wei ^{[1
]}

Feng, Qianjin ^{[1
]}

Chen, Wufan ^{[1
]}

Zhang, Yu ^{[1
]}

机构：

[1] Southern Med Univ, Sch Biomed Engn, Guangzhou 510515, Guangdong, Peoples R China

来源：

PHYSICS IN MEDICINE AND BIOLOGY | 2015年 / 60卷 / 15期

基金：

中国国家自然科学基金;

关键词：

patch-based; adaptive selection; super resolution; IMAGE-RECONSTRUCTION; SUPERRESOLUTION IMAGE; SPARSE REPRESENTATION; REGISTRATION; MOTION; VIDEO; MRI; TIME;

D O I：

10.1088/0031-9155/60/15/5939

中图分类号：

R318 [生物医学工程];

学科分类号：

0831 ;

摘要：

Image enhancement of lung four-dimensional computed tomography (4D-CT) data is highly important because image resolution remains a crucial point in lung cancer radiotherapy. In this paper, we proposed a method for lung 4D-CT super resolution (SR) by using an adaptive-patch-based projection onto convex sets (POCS) approach, which is in contrast with the global POCS SR algorithm, to recover fine details with lesser artifacts in images. The main contribution of this patch-based approach is that the interfering local structure from other phases can be rejected by employing a similar patch adaptive selection strategy. The effectiveness of our approach is demonstrated through experiments on simulated images and real lung 4D-CT datasets. A comparison with previously published SR reconstruction methods highlights the favorable characteristics of the proposed method.

引用

页码：5939 / 5954

页数：16

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