{"title":"医学中的神经网络","authors":"R. Logeswaran","doi":"10.4018/978-1-60566-705-8.ch006","DOIUrl":null,"url":null,"abstract":"Automatic detection of tumours in the bile ducts of the liver is very difficult as often, in the de-facto non-invasive diagnostic images using magnetic resonance cholangiopancreatography (MRCP), tumours are not clearly visible. Specialists use their experience in anatomy to diagnose a tumour by absence of expected structures in the images. Naturally, undertaking such diagnosis is very difficult for an automated system. This chapter proposes an algorithm that is based on a combination of the manual diagnosis principles along with nature-inspired image processing techniques and artificial neural networks (ANN) to assist in the preliminary diagnosis of tumours affecting the bile ducts in the liver. The results obtained show over 88% success rate of the system developed using an ANN with the multi-layer perceptron (MLP) architecture, in performing the difficult automated preliminary detection of the tumours, even in the robust clinical test images with other biliary diseases present.","PeriodicalId":222582,"journal":{"name":"Nature-Inspired Informatics for Intelligent Applications and Knowledge Discovery","volume":"50 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"10","resultStr":"{\"title\":\"Neural Networks in Medicine\",\"authors\":\"R. Logeswaran\",\"doi\":\"10.4018/978-1-60566-705-8.ch006\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Automatic detection of tumours in the bile ducts of the liver is very difficult as often, in the de-facto non-invasive diagnostic images using magnetic resonance cholangiopancreatography (MRCP), tumours are not clearly visible. Specialists use their experience in anatomy to diagnose a tumour by absence of expected structures in the images. Naturally, undertaking such diagnosis is very difficult for an automated system. This chapter proposes an algorithm that is based on a combination of the manual diagnosis principles along with nature-inspired image processing techniques and artificial neural networks (ANN) to assist in the preliminary diagnosis of tumours affecting the bile ducts in the liver. The results obtained show over 88% success rate of the system developed using an ANN with the multi-layer perceptron (MLP) architecture, in performing the difficult automated preliminary detection of the tumours, even in the robust clinical test images with other biliary diseases present.\",\"PeriodicalId\":222582,\"journal\":{\"name\":\"Nature-Inspired Informatics for Intelligent Applications and Knowledge Discovery\",\"volume\":\"50 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"10\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Nature-Inspired Informatics for Intelligent Applications and Knowledge Discovery\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.4018/978-1-60566-705-8.ch006\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Nature-Inspired Informatics for Intelligent Applications and Knowledge Discovery","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.4018/978-1-60566-705-8.ch006","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Automatic detection of tumours in the bile ducts of the liver is very difficult as often, in the de-facto non-invasive diagnostic images using magnetic resonance cholangiopancreatography (MRCP), tumours are not clearly visible. Specialists use their experience in anatomy to diagnose a tumour by absence of expected structures in the images. Naturally, undertaking such diagnosis is very difficult for an automated system. This chapter proposes an algorithm that is based on a combination of the manual diagnosis principles along with nature-inspired image processing techniques and artificial neural networks (ANN) to assist in the preliminary diagnosis of tumours affecting the bile ducts in the liver. The results obtained show over 88% success rate of the system developed using an ANN with the multi-layer perceptron (MLP) architecture, in performing the difficult automated preliminary detection of the tumours, even in the robust clinical test images with other biliary diseases present.