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CADe and CADx systems for lung cancer have been important areas of research in recent decades. However, these research areas are being worked on separately. According to Fraioli et al. [20] one of the main problems of CADe systems for pulmonary nodules is that they detect the nodules but do not characterize them. Thus, computer systems that only detect nodules are not enough for clinical application. Currently, CADe systems do not present the radiological characteristics of the tumor, resulting in lack of information for radiologists, and CADx systems do not detect tumor and do not have good levels of automation [21]. This way, the new CAD should incorporate into a single software a system for detection (CADe) as well as diagnosis (CADx) [20, 22].
Suzuki Diagnostic System Software Download
At the beginning of the segmentation process, the user must inform two points (called seeds) in the image that corresponds to pixels that are inside the right and left lung. In sequence, a pre-processing filter is assigned, called Curvature Flow, to eliminate noise in the image. This filter is an algorithm of finite differences proposed by Sethian [25] and implemented by the Insight Segmentation and Registration Toolkit (ITK) [26]. ITK is an open-source, cross-platform system that provides an extensive suite of software tools for image analysis. 2ff7e9595c
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