Hi
I want to do feature extraction from an image.
I read a paper and did this steps:
I did image segmentation. Then I want to do feature extraction.
In this paper:
Segmented lungs were divided into 3*3 windows in which all nine pixels were located in the lung mask. Window size selection is a compromise between higher resolution (in the classification process) and faster algorithm. Smaller windows (i.e. 1*1 or 2*2) have the problem of more time complexity for training
and increaseing the number of FP. Larger windows (i.e. 5* 5 or larger) cause lower resolution of reconstructed image after
classification and miss some tiny nodules. Thus, for better resolution and faster algorithm, simultaneously, we used a 3*3
window. In the training process, these windows were labeled as nodule (þ1) and non-nodule (1).
My question is this:
Is there any standard criteria to lable the 3*3 window as a noudle? ( I mean if how many of these pixcles are 1, we should lable the window as a noudle?)
What I have tried:
I tried to do feature extraction from an image