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Description
First of all, I'd like to thank you for your amazing work. Your contributions to our field are outstanding.
Issue
I am currently working on a project using CONCH (commit 02d6ac5) and wanted to make sure my WSI analysis pipeline is implemented correctly. I first performed a sanity check using the CRC100k validation set and achieved results similar to those reported in the paper. However, I am stuggling to reproduce the TCGA BRCA results.
Dataset Selection
I downloaded 75 slides of each ILC and IDC (morphology codes 8500/3 and 8520/3). Since I could not find further information about the case or slide IDs used, I did not apply any additional selection criteria.
Embedding Extraction
I computed embeddings using create_embeddings.py from the MADELEINE repository (commit 3a5e9c8
) - I am aware that a February update now recommends using TRIDENT instead, so that will be my next step in debugging. I did not find details about the magnification levels used, so for now I computed embeddings at 40x, 10x and 5x.
Setup
Torch: 2.4.1+cu118
GPU: Nvidia Tesla T4 (16 GB RAM)
CPU: 16-core AMD EPYC 7282
Operating System: Ubuntu 22.04.4 LTS,
Results
Using prompt ensembling with the prompts and templates provided in the paper and the MIZero notebook (commit 02d6ac5), I obtained the following zeroshot classification results:
5x: acc: 0.765 bacc: 0.762 weighted_f1: 0.763 roc_auc: 0.79
10x: acc: 0.720 bacc: 0.720 weighted_f1: 0.710 roc_auc: 0.819
40x: acc: 0.561 bacc: 0.527 weighted_f1: 0.428 roc_auc: 0.666
Questions
The results are lower than those reported in your paper. Could you please give me some input on the following?
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Are these differences within the expected variance due to dataset differences?
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At what magnification did you extract your embeddings?
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Is there any WSI benchmark dataset available for testing the MIZero pipeline?
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Could the discrepancy be due to using the older embedding script from MADELEINE instead of TRIDENT?
Thanks again for your time and for making these tools available!