Finding pairs of images (homologous chromosomes)

[Jean-Patrick Pommier]

Dear All,

I am trying to make pairs of images from the following set of images 
(chromosomes sorted by size after rotation). The idea is to make a feature 
vector for unsupervised classification (kmeans with 19 clusters)


>From each chromosome an integral image was calculated:

plt.figure(figsize = (15,15))
gs1 = gridspec.GridSpec(6,8)
gs1.update(wspace=0.0, hspace=0.0) # set the spacing between axes. 
for i in range(38):
   # i = i + 1 # grid spec indexes from 0
    ax1 = plt.subplot(gs1[i])
    plt.axis('off')
    ax1.set_xticklabels([])
    ax1.set_yticklabels([])
    ax1.set_aspect('equal')
    image = sk.transform.integral_image(reallysorted[i][:,:,2])
    imshow(image , interpolation='nearest')

Then each integral image was flatten and combined with the others:

Features =[]

for i in range(38):
    Feat = 
np.ndarray.flatten(sk.transform.integral_image(reallysorted[i][:,:,2]))
    Features.append(Feat)
X = np.asarray(Features)
print X.shape

The X array contains *38* lines and 9718 features, which is not good. 
However, I trried to submit these raw features to kmeans classification 
with sklearn using a direct example 
<http://scikit-learn.org/stable/modules/neighbors.html> :

from sklearn.neighbors import NearestNeighbors
nbrs = NearestNeighbors(n_neighbors=*19*, algorithm='ball_tree').fit(X)
distances, indices = nbrs.kneighbors(X)
connection = nbrs.kneighbors_graph(X).toarray()
Ploting the connection graph shows that a chromosomes is similar to more 
than one ...

   - Do you think that integral images can be used to discriminate the 
   chromosomes pairs?
   - If so, how to reduce the number of features to 10~20? (to get a better 
   discrimination)
   
Thanks for your advices.

Jean-Patrick

-------------- next part --------------
An HTML attachment was scrubbed...
URL: <http://mail.python.org/pipermail/scikit-image/attachments/20150224/0f542af3/attachment.html>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: pigDAPI_bySize.png
Type: image/png
Size: 80585 bytes
Desc: not available
URL: <http://mail.python.org/pipermail/scikit-image/attachments/20150224/0f542af3/attachment.png>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: IntegralImages.png
Type: image/png
Size: 66034 bytes
Desc: not available
URL: <http://mail.python.org/pipermail/scikit-image/attachments/20150224/0f542af3/attachment-0001.png>
-------------- next part --------------
A non-text attachment was scrubbed...
Name: Connection_graph.png
Type: image/png
Size: 6846 bytes
Desc: not available
URL: <http://mail.python.org/pipermail/scikit-image/attachments/20150224/0f542af3/attachment-0002.png>