5 papers
Predicting Metastatic Risk from Primary Tissue Architecture via Distance-Aware Spatial Modeling
Sandesh Pokhrel, Hamid Manoochehri, Bodong Zhang +2
Predicting the risk of distant metastasis from primary tumor tissue histology is a critical yet challenging task in computational pathology. Multiple Instance Learning (MIL) approa…
Weakly Supervised Contrastive Learning for Histopathology Patch Embeddings
Bodong Zhang, Xiwen Li, Hamid Manoochehri +4
Digital histopathology whole slide images (WSIs) provide gigapixel-scale high-resolution images that are highly useful for disease diagnosis. However, digital histopathology image…
WeakSupCon: Weakly Supervised Contrastive Learning for Encoder Pre-training
Bodong Zhang, Hamid Manoochehri, Xiwen Li +2
Weakly supervised multiple instance learning (MIL) is a challenging task given that only bag-level labels are provided, while each bag typically contains multiple instances. This t…
CLASS-M: Adaptive stain separation-based contrastive learning with pseudo-labeling for histopathological image classification
Bodong Zhang, Hamid Manoochehri, Man Minh Ho +5
Histopathological image classification is an important task in medical image analysis. Recent approaches generally rely on weakly supervised learning due to the ease of acquiring c…
SRA: A Novel Method to Improve Feature Embedding in Self-supervised Learning for Histopathological Images
Hamid Manoochehri, Bodong Zhang, Beatrice S. Knudsen +1
Self-supervised learning has become a cornerstone in various areas, particularly histopathological image analysis. Image augmentation plays a crucial role in self-supervised learni…