How do i calculate Tp, Fp, Dice coefficient for a histopathological image of breast cancer. My code gives accurate results for ultrasound images, but it gives wrong results for tp, fp, and dice? please help me in this.
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i am attaching the evaluation code and image with its ground truth,
function [Jaccard,Dice,rfp,rfn]=sevaluate(m,o)
% gets label matrix for one tissue in segmented and ground truth
% and returns the similarity indices
% m is a tissue in gold truth
% o is the same tissue in segmented image
% rfp false pasitive ratio
% rfn false negative ratio
m=m(:);
o=o(:);
common=sum(m & o);
union=sum(m | o);
cm=sum(m); % the number of voxels in m
co=sum(o); % the number of voxels in o
Jaccard=common/union;
Dice=(2*common)/(cm+co);
rfp=(co-common)/cm;
rfn=(cm-common)/cm;
7 Comments
KALYAN ACHARJYA
on 24 Jul 2018
- First, do the steps for 1 segmentation method, 1 ROC curve
- Second, do the same for another segmentation technique-2nd ROC curve
- So on..you can compare..all ROC curves from ROC space.
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