Docteur de l'université Automatic Segmentation and Shape Analysis ...
Docteur de l'université Automatic Segmentation and Shape Analysis ...
Docteur de l'université Automatic Segmentation and Shape Analysis ...
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18 Chapter 2 Literature Review<br />
Depending on the application <strong>and</strong> imaging modalities used in acquisition, a wi<strong>de</strong><br />
range of segmentation methods has been <strong>de</strong>veloped in or<strong>de</strong>r to <strong>de</strong>al with images<br />
of different parts of body. With respect to the level of human involvement, these<br />
methods can be classified into three categories:<br />
• manual segmentation<br />
• semi-automatic segmentation<br />
• automatic segmentation.<br />
Manual segmentation is usually performed by trained experts following certain<br />
protocols <strong>de</strong>fining regions of interest (ROIs) on the image. The anatomical knowl-<br />
edge of the expert contributes to the segmentation when the boundaries of the<br />
structures are difficult to <strong>de</strong>tect solely based on image features. Although expert-<br />
<strong>de</strong>lineated segmentations are regar<strong>de</strong>d as the ground truth or the gol<strong>de</strong>n st<strong>and</strong>ard,<br />
in practice, manual approaches are subjected to both intra- <strong>and</strong> inter-rater vari-<br />
ability induced by the the human factor. Consi<strong>de</strong>rable variability may result in<br />
low reproducibility of the manual segmentation. In addition, manually tracing the<br />
structures of interest by experts is a laborious task, which can be time consuming<br />
<strong>and</strong> expensive. It might take more than one hour per structure for the expert to<br />
manually <strong>de</strong>fine the boundary of the structure of interest in the volume, which is<br />
impractical <strong>and</strong> inefficient, especially when large data set is involved. Computer<br />
softwares are usually used to assist manual tracing <strong>and</strong> the edition of the bound-<br />
aries, such as the publicly available MRIcron (Ror<strong>de</strong>n <strong>and</strong> Brett, 2000), imageJ<br />
(Abramoff et al., 2004), 3D Slicer (Pieper et al., 2006) <strong>and</strong> ITK-SNAP (Yushkevich<br />
et al., 2006).<br />
Computerized automatic <strong>and</strong> semi-automatic methods are introduced to reduce<br />
the subjectivity in the manual segmentation, <strong>and</strong> to increase the efficiency <strong>and</strong><br />
reproducibility. Semi-automatic segmentation still requires manual operations to<br />
introduce prior knowledge, provi<strong>de</strong> guidance to the process, or correct the segmen-<br />
tation results. The correction of boundaries sometimes can take as long as manual