Discrimitate annotations between radiologists

[ChristianEschen]

Hello

Thanks for this nice software! In the LIDC dataset the contours are created from different radiologists.. Approximately 4 have independently annotated the nodules In order to construct more reliable segmentations /contours it is necessary to discriminate which annotator has annotated the nodules. Is it possible to retrieve information the information about which contours belong to a specific annotator (1,2,3,4)?

[notmatthancock]

The LIDC dataset doesn't assign unique global identifiers to the physical nodules. For a given physical nodule, there may exist up to 4 annotations that refer to it. The annotations are anonymous, so even if it is known that 4 annotations refer to the same nodule, it is impossible to tell which annotator provided each annotation across multiple nodules consistently.

We can estimate when annotations refer to the same physical nodule in a scan by examining the properties of the annotations and clustering them based on the properties. pylidc provides a number of distance metrics between annotations based on the annotation contour coordinates. The Scan model provides a cluster_annotations function which clusters annotations by determining the connected components of the adjacency graph associated with a chosen distance metric and distance tolerance.

Here's an example:

import pylidc as pl

scan = pl.query(pl.Scan).first()
nods = scan.cluster_annotations()

print "Scan is estimated to have", len(nods), "nodules."

for i,nod in enumerate(nods):
    print "Nodule", i+1, "has", len(nod), "annotations."
    for j,ann in enumerate(nod):
        print "-- Annotation", j+1, "centroid:", ann.centroid()

Output:

Scan is estimated to have 4 nodules.
Nodule 1 has 4 annotations.
-- Annotation 1 centroid: [  331.90680101   312.30982368  1480.44962217]
-- Annotation 2 centroid: [  328.60546875   309.91796875  1479.73046875]
-- Annotation 3 centroid: [  327.91666667   309.88293651  1479.01785714]
-- Annotation 4 centroid: [  332.55660377   313.88050314  1479.94339623]
Nodule 2 has 4 annotations.
-- Annotation 1 centroid: [  360.81122449   169.19642857  1542.10459184]
-- Annotation 2 centroid: [  360.82233503   169.21319797  1542.14720812]
-- Annotation 3 centroid: [  361.05243446   168.86142322  1542.34269663]
-- Annotation 4 centroid: [  361.25501433   171.          1542.80659026]
Nodule 3 has 1 annotations.
-- Annotation 1 centroid: [  336.41666667   348.83333333  1545.75      ]
Nodule 4 has 4 annotations.
-- Annotation 1 centroid: [  340.54020979   245.07692308  1606.14160839]
-- Annotation 2 centroid: [  341.29061103   244.65275708  1605.90834575]
-- Annotation 3 centroid: [  341.75417299   244.03490137  1606.95827011]
-- Annotation 4 centroid: [  341.53110048   245.58532695  1606.5       ]

Wait, there's more! You can supply annotation clusters (variable, nods, above) to the scan.visualize function, and arrows will annotate where the nodules are present in the scan.

This comment should be really added to the documentation instead ...

[notmatthancock]

Ok, see here.