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- W101949397 abstract "In this paper, we propose a method for detecting liver cancer from dynamic X-ray CT images. In the diagnosis of a liver, a medical doctor examines dynamic CT images. Dynamic CT images consist of three images namely early phase, portal phase, and late phase, which are taken sequentially within a few minutes. Since the early and late phase images are important for diagnosing liver cancer, our method refers to both of them for detecting suspicious regions and eliminating false positives. At first, the proposed method extracts liver cancer candidates by applying an adaptive neighbor type difference filter from the late phase image. Most of the false positive regions are eliminated by temporal density change feature using both early and late phase images. We applied the proposed method to 21 dynamic CT images. The result showed that sensitivity was 100% and false positives were 0.3 per case in average." @default.
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- W101949397 date "2005-01-01" @default.
- W101949397 modified "2023-09-27" @default.
- W101949397 title "Detection of Liver Cancer based on a Temporal Density Feature from Dynamic X-ray CT Images" @default.
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