UNASSIGNED: 4248 Background: @entity788 is the second most common @entity344 in the Unites States, where it ranks 4(th) among all @entity5 as a cause of @entity204 . There is no screening program for this @entity5 . We describe a non-invasive, semi-automated approach to screening. METHODS: Images were registered using the method of maximization of mutual information (MMI) algorithms. The MMI algorithm is automated and requires no prior processing of the images as is commonly required for a number of existing registration techniques. For this study, a few points from the pancreatic region were used to trace out the entire pancreas. The image segmentation is based on the integration of edge and region information. A homogeneity criterion based on clustering analysis and convex hull construction is used for pancreas detection. Both CT and MRI images of the pancreas from 10 subjects with @entity788 were used. RESULTS: The image registration algorithm was able to realign both CT and MRI pancreatic images within 1mm accuracy in 9 of the 10 subjects. The region-growing algorithm was also able to reliably outline the entire pancreas after a few seed pixels from the pancreas were selected. Using the thresholding algorithm using Otsu's method, a difference between the healthy tissues and cancerous tissue was observed. A bimodal distribution was observed. A clustering method was then used to determine the cancerous region. CONCLUSIONS: In conclusion, semi-automated methods for analyzing multimodal images of the pancreas is presented. Results obtained from this will not only lead to assisting clinicians in detecting and overlaying of pancreatic images, but will also lead to more quantitative analysis. No significant financial relationships to disclose.

Semi-automated method for detecting XXXX in pancreas.

@entity5 :: ('MESH:D009369', 'Disease') :: ['cancers', 'cancer'] @entity788 :: ('MESH:D010190', 'Disease') :: ['Pancreatic cancer', 'pancreatic cancer'] @entity204 :: ('MESH:D003643', 'Disease') :: ['death'] @entity344 :: ('MESH:D005767', 'Disease') :: ['gastrointestinal malignancy']
@entity5 :: (MESH:D009369,Disease) :: ['cancer']
