There is limited development of automatic approaches for the detection and/or diagnosis of pancreatic cancer either from CT or other imaging modalities. This is certainly an area worthy of further investigation and an area identified as in great need of technological advances by the NCI Review Group . Imaging priorities set by the Group have been summarized earlier in this chapter. One of the most interesting recommendation was for a collaborative research and training approach that will link molecular biology, pathology, and imaging as well as for a well documented source of images to support computer applications and image processing .
A few common stages may be identified in all algorithms designed for medical imaging applications, including those designed for assisting the interpretation of CT scans. Figure 4.5 presents the basic modules of an algorithm that aims at assisting the physicians in the interpretation of CT images for the detection, diagnosis, and surveillance of disease. Registration and 3-D reconstruction may precede or follow the last stage of "Processing" (shown in Fig. 4.5) depending on
the goals of the development. Herein we focus on issues related to 2-D CT processing and, hence, registration and reconstruction will not be discussed other than to mention that significant work exists in the area of CT slice registration and reconstruction but is not necessarily focused on pancreatic imaging [39, 40]. We should also note that registration is necessary to the evaluation of serial (temporal) images of the same patient. For example, in the case of segmentation of the pancreas in multiple, serial scans of a patient that undergoes treatment, registration of CT images obtained at different times may be necessary prior to the assessment of changes from one scan to the next. In the following paragraphs, we will examine each module of the CT image processing algorithm (shown in Fig. 4.5) in more detail.
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