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cvlab-stonybrook / SAMPath

Repository for "SAM-Path: A Segment Anything Model for Semantic Segmentation in Digital Pathology" (MedAGI2023, MICCAI2023 workshop)
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How to convert instance-level masks to semantic masks in the CRAG dataset? #23

Open li-qi-lin opened 3 weeks ago

li-qi-lin commented 3 weeks ago

I am currently working with the CRAG dataset, which provides instance-level segmentation masks of adenocarcinoma and benign glands in colon cancer.

I would like to know how to convert these instance-level masks to semantic masks in your experiment.

Could you provide some guidance or suggestions on how to achieve this?

Thank you！

jingweizhang-xyz commented 3 weeks ago

Simply regard all instances as one class: gland and regard the rest region as background.

li-qi-lin commented 2 weeks ago

Thank you！But I still have some questions.

1、The paper of CRAG mentions both healthy and malignant glands, but it isn’t entirely clear if there’s a need to further differentiate these regions within each gland.

2、If additional differentiation within glands is recommended, could you please provide guidance or any established criteria for such annotations?

Understanding this distinction would be very helpful for correctly interpreting and using the mask labels in the dataset. Thank you for your assistance!

jingweizhang-xyz commented 2 weeks ago
  1. We did not try to distinguish between healthy and malignant. If you have such labels, you can have a try.
  2. I do not know about such criteria or annotations.