matlab图像分割肿瘤代码-BMED6780:医学图像处理

[{"title":"（ 32 个子文件 162KB ） matlab图像分割肿瘤代码-BMED6780:医学图像处理","children":[{"title":"BMED6780-master","children":[{"title":"featurerank.m <span style='color:#111;'> 1.55KB </span>","children":null,"spread":false},{"title":"ojaghi_A_Main.m <span style='color:#111;'> 15.76KB </span>","children":null,"spread":false},{"title":"SupervisedSegmentation.m <span style='color:#111;'> 2.72KB </span>","children":null,"spread":false},{"title":"FeatureExtraction_BMED6780.m <span style='color:#111;'> 10.40KB </span>","children":null,"spread":false},{"title":"normal2.m <span style='color:#111;'> 4.61KB </span>","children":null,"spread":false},{"title":"Makingref.m <span style='color:#111;'> 2.80KB </span>","children":null,"spread":false},{"title":"pipeline.m <span style='color:#111;'> 412B </span>","children":null,"spread":false},{"title":"nucleidetector.m <span style='color:#111;'> 17.64KB </span>","children":null,"spread":false},{"title":"myclassifier.mlapp <span style='color:#111;'> 77.52KB </span>","children":null,"spread":false},{"title":"metrics.m <span style='color:#111;'> 600B </span>","children":null,"spread":false},{"title":"ICU_GUI.fig <span style='color:#111;'> 36.79KB </span>","children":null,"spread":false},{"title":"shapefeatures1.m <span style='color:#111;'> 3.64KB </span>","children":null,"spread":false},{"title":"Kmeansmethod.m <span style='color:#111;'> 1.94KB </span>","children":null,"spread":false},{"title":"normal3.m <span style='color:#111;'> 2.29KB </span>","children":null,"spread":false},{"title":"normal.m <span style='color:#111;'> 3.66KB </span>","children":null,"spread":false},{"title":"batchnormal.m <span style='color:#111;'> 2.05KB </span>","children":null,"spread":false},{"title":"LDA.m <span style='color:#111;'> 2.24KB </span>","children":null,"spread":false},{"title":"shapefeatures2.m <span style='color:#111;'> 3.65KB </span>","children":null,"spread":false},{"title":"FeatExt.m <span style='color:#111;'> 1.82KB </span>","children":null,"spread":false},{"title":"trainclassifier.m <span style='color:#111;'> 6.35KB </span>","children":null,"spread":false},{"title":"imagetraining.m <span style='color:#111;'> 8.74KB </span>","children":null,"spread":false},{"title":"mycnn.m <span style='color:#111;'> 5.27KB </span>","children":null,"spread":false},{"title":"Featureextraction_Final.m <span style='color:#111;'> 1.14KB </span>","children":null,"spread":false},{"title":"batchnormal3.m <span style='color:#111;'> 4.36KB </span>","children":null,"spread":false},{"title":"RGB_Histogram_Demo.m <span style='color:#111;'> 7.85KB </span>","children":null,"spread":false},{"title":"rgb_hist.m <span style='color:#111;'> 2.09KB </span>","children":null,"spread":false},{"title":"README.md <span style='color:#111;'> 3.17KB </span>","children":null,"spread":false},{"title":"featextract_all.m <span style='color:#111;'> 3.04KB </span>","children":null,"spread":false},{"title":"segmentation.m <span style='color:#111;'> 653B </span>","children":null,"spread":false},{"title":"KmeansSegmentation.m <span style='color:#111;'> 5.93KB </span>","children":null,"spread":false},{"title":"evaluate.m <span style='color:#111;'> 2.87KB </span>","children":null,"spread":false},{"title":"knnalgorithm.m <span style='color:#111;'> 6.35KB </span>","children":null,"spread":false}],"spread":false}],"spread":true}]