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Pulmonary nodule registration in serial CT scans based on rib anatomy and nodule template matching
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Image of FIG. 1.
FIG. 1.

Flowchart for our pulmonary nodule registration method in two serial CT scans.

Image of FIG. 2.
FIG. 2.

Flowchart of the rib segmentation method.

Image of FIG. 3.
FIG. 3.

Bone segmentation for starting points of the rib tracking. (a) A series of small regions containing the spine and portions of the fifth rib pair. The slices are ordered from left to right and top to bottom. (b) Segmentation results of the series of small regions in (a). They were used to determine the starting locations of the fifth rib pair.

Image of FIG. 4.
FIG. 4.

Profile for the rib starting locations along the spine. The coordinate stands for the CT slice number in the ascending order from the neck to the abdomen. The coordinate , where the fifth rib pair joins the fifth thoracic vertebra, is indicated by the arrow.

Image of FIG. 5.
FIG. 5.

The slice where the lung apex starts to appear. This slice was used as the reference for labeling the second rib pair.

Image of FIG. 6.
FIG. 6.

Rib centerlines after segmentation, labeling, and skeletonization. The first rib pair is not involved in nodule registration and is not segmented.

Image of FIG. 7.
FIG. 7.

(a) A slice of the 3D lung volume. Two nodules are identified by the boxes. (b) The 3D Hessian responses on the same slice as in (a). The nodules are discernible in (b), whereas many of the vessels have been suppressed.

Image of FIG. 8.
FIG. 8.

The size of pulmonary nodules, as measured by an experienced chest radiologist, on the source (prior) and target (current) scans. Because the exact size is difficult to measure for small lesions, nodules with a diameter less than are plotted at a diameter of .

Image of FIG. 9.
FIG. 9.

(a) Histogram of the Euclidean distance errors after the 3D rigid affine transformation, and the final error after refinement by template matching with the geometrical constraint. (b) Distribution of the cross-correlation coefficient between the nodule templates in the source scan and the registered location in the target scan. To show the positive cross-correlation coefficients in detail, all negative cross-correlation coefficients were grouped to the bar representing . (c) Scatter-plot of the Euclidean distance errors and the cross-correlation coefficients. Nodule A is misregistered due to the 3D rigid affine transformation and template matching and nodule B is misregistered due to template matching.

Image of FIG. 10.
FIG. 10.

(a) Histogram of the volume overlap ratios. Only the outliers nodule A and nodule B have zero overlap. (b) The scatter-plot of the volume overlap ratios and the cross-correlation coefficients. A nodule with a high cross-correlation coefficient typically has a high volume overlap ratio. (c) Scatter-plot of the Euclidean distance error and the volume overlap ratio. The two outliers nodule A and nodule B have large distance errors and zero overlap.

Image of FIG. 11.
FIG. 11.

Two CT scans of the same patient, acquired at an interval of : (a) source scan and (b) target scan. Nodule A was identified by an experienced chest radiologist as marked by the box in each image. This is a small juxta-pleural nodule and there is apparently a significant location change between the two scans. Nodule A is one of the outliers that was misregistered in our study.

Image of FIG. 12.
FIG. 12.

The CT image in the target scan and the Hessian response for the outlier nodule B, identified by the box in each image. Notice that the nodule is small with a diameter of and its shape is distorted by the neighboring vessels. Nodule B is one of the outliers that was misregistered in our study.


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Registration performance under different criteria for different techniques.


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752b84549af89a08dbdd7fdb8b9568b5 journal.articlezxybnytfddd
Scitation: Pulmonary nodule registration in serial CT scans based on rib anatomy and nodule template matching