11 papers
Data-driven registration and modeling of brain deformation for image-guided neurosurgery
Tiago Assis, Colin P. Galvin, Joshua P. Castillo +12
Accurate compensation of brain deformation is critical for reliable image-guided neurosurgery. Surgical manipulation and tumor resection induce tissue motion, causing preoperative…
AGE-MIL: Anchor-Guided Evidence Learning for Patient-Level Prediction
Jiawei Niu, Jian Chen, Di Zhang +8
Existing computational pathology methods predominantly operate within whole-slide image (WSI)-level multiple instance learning (MIL) paradigms, while patient-level modeling remains…
Thinking in Scales: Accelerating Gigapixel Pathology Image Analysis via Adaptive Continuous Reasoning
Jiusong Ge, Yingkang Zhan, Wenjie Zhao +13
Traditional whole slide image (WSI) analysis methods typically rely on the multiple instance learning (MIL) paradigm, which extracts patch-level features at high magnification and…
Vision Transformers for Preoperative CT-Based Prediction of Histopathologic Chemotherapy Response Score in High-Grade Serous Ovarian Carcinoma
Francesca Fati, Felipe Coutinho, Marika Reinius +25
Purpose. High-grade serous ovarian carcinoma (HGSOC) is characterized by pronounced biological and spatial heterogeneity and is frequently diagnosed at an advanced stage. Neoadjuva…
CARE: A Molecular-Guided Foundation Model with Adaptive Region Modeling for Whole Slide Image Analysis
Di Zhang, Zhangpeng Gong, Xiaobo Pang +14
Foundation models have recently achieved impressive success in computational pathology, demonstrating strong generalization across diverse histopathology tasks. However, existing m…
Developing Predictive and Robust Radiomics Models for Chemotherapy Response in High-Grade Serous Ovarian Carcinoma
Sepideh Hatamikia, Geevarghese George, Florian Schwarzhans +10
Objectives: High-grade serous ovarian carcinoma (HGSOC) is typically diagnosed at an advanced stage with extensive peritoneal metastases, making treatment challenging. Neoadjuvant…