An automated CT based lung nodule detection scheme using geometric analysis of signed distance field.
The authors present a new computerized scheme to automatically detect lung nodules depicted on computed tomography (CT) images. The procedure is performed in the signed distance field of the CT images. To obtain an accurate signed distance field, CT images are first interpolated linearly along the axial direction to form an isotropic data set. Then a lung segmentation strategy is applied to smooth the lung border aiming to include as many juxtapleural nodules as possible while minimizing over segmentations of the lung regions. Potential nodule regions are then detected by locating local maximas of signed distances in each subvolume with values and the sizes larger than the smallest nodule of interest in the three-dimensional space. Finally, all detected candidates are scored by computing the similarity distance of their medial axis-like shapes obtained through a progressive clustering strategy combined with a marching cube algorithm from a sphere based shape. A free-response receiver operating characteristics curve is computed to assess the scheme performance. A performance test on 52 low-dose CT screening examinations that depict 184 verified lung nodules showed that during the initial stage the scheme achieved an asymptotic maximum sensitivity of 95.1% (175/184) with an average of 1200 suspicious voxels per CT examination. The nine missed nodules included two small solid nodules (with a diameter < or =3.1 mm) and seven nonsolid nodules. The final performance level after the similarity scoring stage was an absolute sensitivity level, namely, including the nine missed during the initial stage, of 81.5% (150/184) with 6.5 false-positive identifications per CT examination. This preliminary study demonstrates the feasibility of applying a simple and robust geometric model using the signed distance field to identify suspicious lung nodules. In the authors' data set the sensitivity of this scheme is not affected by nodule size. In addition to potentially being a stand alone approach, the signed distance field based method can be easily implemented as an initial filtering step in other computer-aided detection schemes.
Pu
Jiantao
J
Imaging Research Center, Department of Radiology University of Pittsburgh, Pittsburgh, Pennsylvania 15213, USA. puj@upmc.edu
Zheng
Bin
B
Leader
Joseph Ken
JK
Wang
Xiao-Hui
XH
Gur
David
D
D000818:Animals; D005189:False Positive Reactions; D006801:Humans; D008175:Lung Neoplasms / Q000000981:diagnostic imaging / Q000473:pathology*; D010363:Pattern Recognition, Automated / Q000379:methods*; D011856:Radiographic Image Enhancement / Q000379:methods; D011857:Radiographic Image Interpretation, Computer-Assisted / Q000379:methods; D012680:Sensitivity and Specificity; D014057:Tomography, X-Ray Computed / Q000379:methods*
IEEE Trans Vis Comput Graph. 2006 Jul-Aug;12(4):581-99
16805266
J Appl Clin Med Phys. 2003 Summer;4(3):248-60
12841796
Med Phys. 1999 Jun;26(6):889-95
10436889
AJR Am J Roentgenol. 2005 Oct;185(4):973-8
16177418
IEEE Trans Med Imaging. 2001 Jul;20(7):595-604
11465466
Med Phys. 2003 Aug;30(8):2040-51
12945970
IEEE Trans Med Imaging. 1990;9(1):32-42
18222748
IEEE Trans Med Imaging. 2000 Jul;19(7):711-21
11055786
IEEE Trans Med Imaging. 2005 Mar;24(3):409-23
15754991
Radiol Clin North Am. 2003 May;41(3):575-97, vi
12797607
IEEE Trans Med Imaging. 2004 Jun;23(6):661-75
15191141
Eur Radiol. 2003 Oct;13(10):2378-83
12743736
Radiology. 1996 Dec;201(3):798-802
8939234
Med Phys. 2001 Oct;28(10):2070-6
11695768
Proc Natl Acad Sci U S A. 1996 Feb 20;93(4):1591-5
11607632
Lung Cancer. 2003 Dec;42(3):291-6
14644516
Med Phys. 2003 Jul;30(7):1602-17
12906178
Radiographics. 1999 Sep-Oct;19(5):1303-11
10489181
Radiology. 2001 Jan;218(1):267-73
11152813
Comput Biol Med. 2007 Aug;37(8):1167-72
17182027
Radiology. 1999 Oct;213(1):289-98
10540674
IEEE Trans Med Imaging. 2001 Jun;20(6):490-8
11437109
Med Phys. 2001 Aug;28(8):1552-61
11548926
Invest Radiol. 1994 Apr;29(4):459-65
8034453
Radiology. 2005 Jan;234(1):274-83
15537839
IEEE Trans Med Imaging. 2001 Dec;20(12):1242-50
11811824
Med Phys. 2006 Apr;33(4):1133-40
16696491
IEEE Trans Med Imaging. 1992;11(4):507-16
18222892
Radiology. 1994 Apr;191(1):257-62
8134584