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Erschienen in:
2018 | OriginalPaper | Buchkapitel
Classification of Pancreatic Cystic Neoplasms Based on Multimodality Images
verfasst von : Weixiang Chen, Hongchen Ji, Jianjiang Feng, Rong Liu, Yi Yu, Ruiquan Zhou, Jie Zhou
Erschienen in: Machine Learning in Medical Imaging
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Abstract
Classification of pancreatic cystic neoplasms (PCN) into subclasses is crucial since their treatments are different. However, accurate classification is very difficult even for radiologists, due to similar appearance and shape. We propose a network called PCN-Net which makes use of T1/T2 MRI of abdomen by its three stages design. The first and second stages are trained on T1 and T2 separately for detection and inter-modality registration. After a Z-Continuity Filter and modalities fusion, the third stage predict the results with registered image pairs. On a database of 48 patients, our method can predict with slice level accuracy of \(80.0\%\) and patient level accuracy of \(92.3\%\), which are much better than other baseline methods.