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Journal of Medical Systems

, 33:413 | Cite as

Cholangiocarcinoma—An Automated Preliminary Detection System Using MLP

  • Rajasvaran Logeswaran
Original Paper

Abstract

Cholangiocarcinoma, cancer of the bile ducts, is often diagnosed via magnetic resonance cholangiopancreatography (MRCP). Due to low resolution, noise and difficulty is actually seeing the tumor in the images, especially by examining only a single image, there has been very little development of automated systems for cholangiocarcinoma diagnosis. This paper presents a computer-aided diagnosis (CAD) system for the automated preliminary detection of the tumor using a single MRCP image. The multi-stage system employs algorithms and techniques that correspond to the radiological diagnosis characteristics employed by doctors. A popular artificial neural network, the multi-layer perceptron (MLP), is used for decision making to differentiate images with cholangiocarcinoma from those without. The test results achieved was 94% when differentiating only healthy and tumor images, and 88% in a robust multi-disease test where the system had to identify the tumor images from a large set of images containing common biliary diseases.

Keywords

Magnetic resonance cholangiopancreatography (MRCP) Cancer Tumor Bile ducts Computer-aided diagnosis 

Notes

Acknowledgment

This paper is supported by the Soongsil University Research Fund.

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Copyright information

© Springer Science+Business Media, LLC 2008

Authors and Affiliations

  1. 1.Global School of MediaSoongsil UniversitySeoulSouth Korea
  2. 2.Faculty of EngineeringMultimedia UniversityCyberjayaMalaysia

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