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eess.IV2023★ 1 cited
DPSeq: A Novel and Efficient Digital Pathology Classifier for Predicting Cancer Biomarkers using Sequencer Architecture
Min Cen, Xingyu Li, Bangwei Guo +3
In digital pathology tasks, transformers have achieved state-of-the-art results, surpassing convolutional neural networks (CNNs). However, transformers are usually complex and reso…
eess.IV2022★ 13 cited
Colorectal cancer survival prediction using deep distribution based multiple-instance learning
Xingyu Li, Jitendra Jonnagaddala, Min Cen +2
Several deep learning algorithms have been developed to predict survival of cancer patients using whole slide images (WSIs).However, identification of image phenotypes within the W…
eess.IV2022
Improving Feature Extraction from Histopathological Images Through A Fine-tuning ImageNet Model
Xingyu Li, Min Cen, Jinfeng Xu +2
Due to lack of annotated pathological images, transfer learning has been the predominant approach in the field of digital pathology.Pre-trained neural networks based on ImageNet da…