ymli39
commented
1 year ago Hi sorry about the late response, I just fixed the bug in the file "noduleCADEvaluationLUNA16.py", I have added fold9 csv for test (/luna_detector/labels/luna_test.csv), you can directly run noduleCADEvaluationLUNA16.py to generate the results. The results should match the one that I uploaded.
update: The missing nodules in file "nodulesWithoutCandidate_predanno0.3.txt." should be:
237,None,56.58885682,-67.46153204,-77.34666348,3.270466947,-1 612,None,-6.607170093,22.55937329,-143.7929641,9.484890340,-1 612,None,116.8024039,-1.291850522,-197.5054168,4.666322736,-1 612,None,119.2088976,-11.4328236,-208.2932951,6.853377495,-1 612,None,111.5336493,-37.25625083,-238.8281758,5.772283337,-1 612,None,95.99601184,-23.33441995,-157.7220192,4.835148932,-1
Hi, Thanks for sharing your codes and thanks for your good paper. I use the predanno0.3.csv provided by you, and according to luna_ Test.npy has made the corresponding CSV file. I found that the FROC scores of 0.125, 0.25, 0.5 and 0.1 are lower than expected. Do you have any good suggestions? I evaluated the CSV detection file provided by you.
Total number of included nodule annotations: 86 Total number of nodule annotations: 3596 (1000, 10000) ########################## 0.47112617 0.125 0.60532993 0.25 0.74687976 0.5 0.8357665 1.0 0.9013603 2.0 0.9310172 4.0 0.93185717 8.0 0.77476245 0.7691029900332226 16.0
CAD Analysis: predanno0.3
Candidate detection results: True positives: 83 False positives: 1443 False negatives: 6 True negatives: 0 Total number of candidates: 1770 Total number of nodules: 89 Ignored candidates on excluded nodules: 230 Ignored candidates which were double detections on a nodule: 14 Sensitivity: 0.932584270 Average number of candidates per scan: 19.450549451