Hongming Xu

Spatial heterogeneity and organization of tumor mutation burden and immune infiltrates within tumors based on whole slide images correlated with patient survival in bladder cancer

The paper uses whole slide images to analyze spatial heterogeneity of tumor mutation burden and immune infiltrates in bladder cancer, finding that low spatial heterogeneity with high TILs correlates with improved survival.

Spatial analysis of tumor infiltrating lymphocytes based on deep learning using histopathology image to predict progression-free survival in colorectal cancer

This paper uses deep learning to analyze histopathology images of colorectal cancer to predict progression-free survival by quantifying tumor infiltrating lymphocytes.

Fraction and Spatial Organization of Tumor-Infiltrating Lymphocytes Correlating with Bladder Cancer Patient Survival

This paper develops a CNN-based method to analyze TILs in bladder cancer WSIs, showing their fraction and spatial organization correlate with patient survival.

STATISTICAL LOCAL BINARY PATTERNS (SLBP): APPLICATION TO PROSTATE CANCER GLEASON SCORE PREDICTION FROM WHOLE SLIDE PATHOLOGY IMAGES

This paper introduces a texture descriptor called SLBP for prostate cancer Gleason score prediction from whole slide images, achieving over 80% accuracy in distinguishing grades ≤7 vs ≥8.

Gaussian Process Based Heteroscedastic Noise Modeling for Tumor Mutation Burden Prediction from Whole Slide Images

This paper develops a Gaussian process-based method for TMB prediction from whole slide images, outperforming baseline methods by incorporating heteroscedastic noise modeling.

Automatic Classification of Prostate Cancer Gleason Scores from Digitized Whole Slide Tissue Biopsies

This paper presents an automatic method for Gleason score classification of prostate cancer using CSLBP descriptors and SVM, achieving over 79% accuracy on TCGA data.