I downloaded version 2 of Task 2 ground truth. After checking the attribute masks (milia like, streaks, etc.) I found that the globules masks (ISIC_XXXXXXX_attribute_globules.png) are completely black images. Therefore, I understand that there are no globules annotations at all in the database. Am I missing something or is this the case?
Additionally, I found this prevalence of images with at least 25 pixels annotated with lesions:
Pigment network: ~58% of the total amount of images
Negative network: ~7% of the total amount of images
Streaks: ~1,5% of the total amount of images
Milia like cyst: ~26% of the total amount of images
Globules: 0% of the total amount of images
Under these conditions, does it make sense to train a system for Streak or Negative network segmentation?
We will investigate this immediately let you know what we find.
Do you have any updates on this issue? Same situation here. The sample scarcity makes it difficult to make correct prediction.
Hello @melanoma and @cx.lavinia ,
Thank you for your patience. I wanted to fully investigate the issue and verify our solution, but we now have an official update:
We recently became aware of an issue where certain attributes were severely under-represented in the ISIC Challenge’s Task 2: Lesion Attribute Detection training ground truth. Accordingly, we’ve re-generated and re-released the training ground truth, after thoroughly re-querying our database for all available ground truth data.
The updated training ground truth bundle may be downloaded from: https://challenge.kitware.com/#phase/5abcbb6256357d0139260e5f , by the filename ISIC2018_Task2_Training_GroundTruth_v3.zip . It is necessary that all Task 2 participants download and use this updated bundle for training algorithms. Please discard all earlier versions of the Task 2 training ground truth bundle. However, the training input data bundle (containing JPEG lesion images) has not changed and does not need to be re-downloaded.
For reference, the image-wise counts of positive attribute instances in this updated data are:
We certainly regret any inconveniences that this may have caused. Please let me know here if you have any further questions or issues.
Thank you very much Brian,
I will try with this new batch. May I ask another related question? I noticed that some Task 2 annotations have been made outside the delineated (annotated) mole region for Task 1. Is this correct?
Thanks in advance
Hi @melanoma ,
Rarely, dermoscopic attributes may be present outside of the image’s primary lesion (perhaps within a secondary lesion within the image), but this is not common.
i found some of the cases like 4, 23, 40, 99, 101, 110 … in latest release of GroundTruth-v3 for Task 2 all the mask images are blank. are they really blank or some correction is to be done?
There are lesions with none of the 5 dermoscopic attributes. These serve as negative examples for training.