- Category:
- AI-NN-PR
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-
- File Size:
- 216kb
- Update:
- 2012-11-26
- Downloads:
- 1 Times
- Uploaded by:
- gaojianrui88
Description: Objective Design and develop a intelligent cytopathological lung cancer diagnosing system(ICLCDS) utilizing the latest computer technologies(including Reinforcement Lcaming Multiple Classifier Fusion and Dimcnsionality Reduction) and the cy-topathological knowledge on lung canccrcclls Methods We got information ofcclls and segregated cell regions in a slice image using an magi scgmcntouon a址orithm Sascd on reinforcement lcaming including rcconstmction of overlapped cell area Sascd on B一Spline and improved dcBoor-Cox Mcthoc} We comSincd multiple classifiers including Baycsian classific:Support Vector Machine(SVM)
classific K-Ncarcst NcighSour( KNN) and Decision c classific to achieve an accurate result of cytopathological lung cancer diag-nosis Results Experimental results on 1 200 cases randomly selected we as follows the accurate diagnosis rate for lung cancer idcn-tification was the false positive rate was 1. 8`J /c‘the false negative rate was 3. 3`J /c‘the type class
- [svmcell] - use SVM optimal algorithm to segment ima
- [cancer-fenxi] - This the analysis of cell morphology in
- [ripley] - This is achieved using MATLAB algorithm
- [delphiblood] - delphi blood red blood cells to identify
- [ordreg] - Based on MATLAB prepared multi-SVM class
- [homework] - PCA+ KNN-based face recognition algorith
- [gyy] - This paper tries to deal with gene expre
- [mill] - Contains a lot of classification algorit
- [netcdf] - code related to the reading, writing and
- [aambuilding-1.0] - aam model, also known as the active perf
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计算机辅助肺癌细胞病理诊断的初步研究.caj
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