3D Reconstruction of the Human Rib Cage from 2D Projection ... - ZIB

3.2. 2D/3D Reconstruction
The recent work of Koehler et al. [KWG09] proposes a template-based approach
to approximate the 3D shape of the ribs from two segmented radiographs (PA
and lateral view). A segmentation of individual ribs, obtained with the method
Figure 3.3: Template fitting according
to Koehler et al: Based on a classification
of anterior, lateral and posterior
parts of the ribs in a segmented
PA view, vertex clusters of a template
assigned to one of the three parts
are fitted to the image data (adopted
from [KWG09]).
of Plourde et al. [PCD06], is classified according
to whether it belongs to the anterior, lateral,
or posterior part of a rib. Based on this
classification, the vertices of a 3D rib template
model are annotated. Then, each rib
is reconstructed individually by aligning the
corresponding parts to the segmented X-ray
image (see Fig. 3.3). The alignment to the
PA-view is subsequently improved by adapting
the template to the outer border of the rib
cage in the lateral view. So far no quantitative
validation of the method is available. Furthermore,
no reliable ground truth was used
to assess the reconstruction accuracy, as the
reconstruction quality is measured by comparing
the area overlap between the segmentation
of the PA-view and the projection of the reconstructed
3D model. However, our experiments
(cf. Sect. 6.2.5 and Fig. 6.8) indicate
that the relation between the model’s match-
ing quality to one PA-view and the actual reconstruction result is highly ambiguous
and, hence, is no adequate basis for a validation.
The method presented in this thesis is similar to the work of Benameur et
al. [BMDDG05], as it uses a 3D SSM and relies on edge-based features in the image
data, instead of landmarks that have little prospect of being detected automatically
from radiographs. However, in contrast to [BMDDG05], we use an SSM of the rib’s
surfaces. The approach, that is proposed in this thesis, allows for a direct comparison
of rib contours in both, the model projection and the image data, where
Benameur et al. propose to compare projected midlines of the model with contours
of the ribs in the image data. Furthermore, in [BMDDG05] 3D reconstructions obtained
with the method of Dansereau and Srokest [DS88] are used as gold standard
to evaluate the method, which limits the assessment of the method’s accuracy. We
use 3D surface models of rib cages, extracted from CT-data of 29 different subjects,
as reliable gold standard in our evaluation.
3.2 2D/3D Reconstruction
In this section, methods for the 3D reconstruction from 2D images are presented that
follow a similar model-based approach as the method presented in this thesis. Work
that primarily addresses the problem of the reconstruction of the pose or the shape
is examined. Most of the described methods are based on the iterative closest point
(ICP) algorithm [BM92], a general method for aligning shapes by generating pairs
of corresponding points between two shapes to be matched. The ICP algorithm and
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