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Computer-aided detection of lung nodules via 3D fast radial transform, scale space representation, and Zernike MIP classification
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10.1118/1.3560427
/content/aapm/journal/medphys/38/4/10.1118/1.3560427
http://aip.metastore.ingenta.com/content/aapm/journal/medphys/38/4/10.1118/1.3560427

Figures

Image of FIG. 1.
FIG. 1.

Schematic block diagram of the proposed CAD system.

Image of FIG. 2.
FIG. 2.

FR algorithm: Positive- and negative-affected points by gradient at point : Radius .

Image of FIG. 3.
FIG. 3.

MIP processing of a stack of images along direction. Maximum value encountered along the axis is assigned to the final image.

Image of FIG. 4.
FIG. 4.

Effects of MIP processing on nodules images. Upper row shows a true positive, while lower row shows a false positive; raw images on the left, while MIP images on the right.

Image of FIG. 5.
FIG. 5.

Feature extraction: MIP generation from 3D volume and extraction of Zernike moments from MIP images.

Image of FIG. 6.
FIG. 6.

Distribution of diameters of the annotated nodules in the studied LIDC database subset.

Image of FIG. 7.
FIG. 7.

FROC curve for the overall CAD performance.

Image of FIG. 8.
FIG. 8.

ANODE09 FROC curves for the presented CAD system.

Tables

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TABLE I.

Distribution of nodule characteristics for AL4. Values in the first column are rounded means of the evaluations given by radiologists for a given nodule. Characteristic value meanings are shown in Table II.

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TABLE II.

Value meanings for LIDC characteristics.

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TABLE III.

CAD system results for the detection part and heuristic FPR at AL 4. Sensitivity and FPs/patient are reported for each module of the CAD.

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TABLE IV.

FROC curve analysis. Sensitivity at various FP/patient rate. Uncertainty estimations are based on binomial proportion using Wilson score interval (Ref. 59) with correction for continuity, with 95% confidence.

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TABLE V.

Sensitivity distribution for different types of nodule characteristics for AL4, in the working point with 71% overall sensitivity. Values in the first column are rounded means of the evaluations given by radiologists for a given nodule. Uncertainty estimations are based on binomial proportion using Wilson score interval (Ref. 59) with correction for continuity, with 95% confidence. Characteristic value meanings are shown in Table II.

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TABLE VI.

Performance comparison with other studies using the LIDC dataset. Sensitivity distribution for different ALs, in the working point with 4 FP/patient, unless differently reported. Uncertainty estimates are shown where available. Reference 50 does not include ground glass opacities (GGOs).

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TABLE VII.

Comparison of scores in ANODE09 study. Assigned scores are calculated as the average of true positive fractions at 1/8, 1/4, 1/2, 1, 2, 4, and 8 FP/patient. This work is referred to as “MIG GROUP.” Compared CAD systems are described in Ref. 18 apart from “Flyer Scan,” which is described in Ref. 57. In this table, nodule types use ANODE09 nomenclature. In particular, juxta-vascular and juxta-pleural nodules are described here as vascular and pleural nodules, respectively.

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/content/aapm/journal/medphys/38/4/10.1118/1.3560427
2011-03-18
2014-04-16
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752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd
Scitation: Computer-aided detection of lung nodules via 3D fast radial transform, scale space representation, and Zernike MIP classification
http://aip.metastore.ingenta.com/content/aapm/journal/medphys/38/4/10.1118/1.3560427
10.1118/1.3560427
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