Iteratively Coupled Multiple Instance Learning from Instance to Bag Classifier for Whole Slide Image Classification

Understand

Whole Slide Image (WSI) classification remains a challenge due to their extremely high resolution and the absence of fine-grained labels.

• Presently, WSI classification is usually regarded as a Multiple Instance Learning (MIL) problem when only slide-level labels are available.
• MIL methods involve a patch embedding module and a bag-level classification module, but they are prohibitively expensive to be trained in an end-to-end manner.
• Therefore, existing methods usually train them separately, or directly skip the training of the embedder.