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binli123
DSMIL: Dual-stream multiple instance learning networks for tumor detection in Whole Slide Image
Hi, Could you upload a patch example with its slide name,x and y position for each magnitude? I m trying to replicate your numbers with even a threshold of 30...
Thanks for the great work! You mentioned that you randomly split 840 training slides and 210 testing slides in the paper. In the train_tcga.py, I noticed that all the slides...
Hello, thank you for your excellent work! Earlier I tried to reproduce the results of Camelyon16, I used a total of 271 training sets, batch size 512 to train simclr...
Hi, thank you very much for sharing this code - I wanted to ask for some guidance on how to set the num_classes parameter. I have a case where each...
Hello, I was wondering if you could describe how you generated the pre-computed features provided in this repository so that i can reproduce the same thing using a different dataset....
Hi,thanks for sharing your great work and it really helps me a lot.I have 2 questions to ask. First,Your paper discusses experiments with 20×+5× multiscale features, showing promising results. However,...
Hi, could you please share with me the distribution of slides used for training and testing in the TCGA dataset, along with their respective labels? I noticed that it's mentioned...
您好，请问使用Camelyon16数据集，使用simclr模型权重文件提取实例特征compute_feats.py该文件 --num_classes是1还是2，提取完实例特征进行mil聚合时，train_tcga.py --num_classes是1还是2，一时没有搞明白，希望您能解答一下 
When inspecting the state dict of milnet in `testing_tcga.py` it has keys `b_classifier.q.0.bias` and `b_classifier.q.2.bias` but the aggregator.pth has keys `b_classifier.q.bias`. It suggests that you trained the aggregator with `nonlinear=False`...
We have encountered challenges in replicating the FROC score calculations. To ensure accuracy and consistency, we would greatly appreciate your assistance with the following inquiries: - Could you kindly provide...
