6 papers
Progressive Translation of H&E to IHC with Enhanced Structural Fidelity
Yuhang Kang, Ziyu Su, Tianyang Wang +3
Compared to hematoxylin-eosin (H&E) staining, immunohistochemistry (IHC) not only maintains the structural features of tissue samples, but also provides high-resolution protein loc…
Hyperparameter Optimization and Reproducibility in Deep Learning Model Training
Usman Afzaal, Ziyu Su, Usama Sajjad +4
Reproducibility remains a critical challenge in foundation model training for histopathology, often hindered by software randomness, hardware non-determinism, and inconsistent hype…
Morphology-Aware Prognostic model for Five-Year Survival Prediction in Colorectal Cancer from H&E Whole Slide Images
Usama Sajjad, Abdul Rehman Akbar, Ziyu Su +5
Colorectal cancer (CRC) remains the third most prevalent malignancy globally, with approximately 154,000 new cases and 54,000 projected deaths anticipated for 2025. The recent adva…
Learning the Language of Histopathology Images reveals Prognostic Subgroups in Invasive Lung Adenocarcinoma Patients
Abdul Rehman Akbar, Usama Sajjad, Ziyu Su +5
Recurrence remains a major clinical challenge in surgically resected invasive lung adenocarcinoma, where existing grading and staging systems fail to capture the cellular complexit…
Predicting Neoadjuvant Chemotherapy Response in Triple-Negative Breast Cancer Using Pre-Treatment Histopathologic Images
Hikmat Khan, Ziyu Su, Huina Zhang +6
Triple-negative breast cancer (TNBC) remains a major clinical challenge due to its aggressive behavior and lack of targeted therapies. Accurate early prediction of response to neoa…
Computational Pathology for Accurate Prediction of Breast Cancer Recurrence: Development and Validation of a Deep Learning-based Tool
Ziyu Su, Yongxin Guo, Robert Wesolowski +4
Accurate recurrence risk stratification is crucial for optimizing treatment plans for breast cancer patients. Current prognostic tools like Oncotype DX (ODX) offer valuable genomic…