8 papers
Light-sheet microscopy to assess cancer pathology: current views and future trends
Uma PisaroviÄ, Taichi Ochi, Iryna Samarska +6
In recent years, light-sheet fluorescence microscopy (LSFM) has emerged as a powerful tool for visualizing and analyzing cancer tissue samples, including patient-derived specimens,…
A Physics-Driven Neural Network with Parameter Embedding for Generating Quantitative MR Maps from Weighted Images
Lingjing Chen, Chengxiu Zhang, Yinqiao Yi +9
We propose a deep learning-based approach that integrates MRI sequence parameters to improve the accuracy and generalizability of quantitative image synthesis from clinical weighte…
Foundation Models -- A Panacea for Artificial Intelligence in Pathology?
Nita Mulliqi, Anders Blilie, Xiaoyi Ji +28
The role of artificial intelligence (AI) in pathology has evolved from aiding diagnostics to uncovering predictive morphological patterns in whole slide images (WSIs). Recently, fo…
Preclinical Water-Mediated Ultrasound Platform using Clinical FOV for Molecular Targeted Contrast-Enhanced Ultrasound
Stavros Melemenidis, Anna Stephanie Kim, Jenny Vo-Phamhi +3
Background: This protocol introduces an ultrasound (US) configuration for whole-body 3D dynamic contrast-enhanced ultrasound (DCE-US) imaging in preclinical applications. The set-u…
A novel imaging setup for hybrid radiotherapy tailored PET/MR in patients with head and neck cancer
R. M. Winter, O. Engelsen, O. J. Bratting +4
Purpose: Radiotherapy commonly relies on CT, but there is growing interest in using hybrid PET/MR. Therefore, dedicated hardware setups have been proposed for PET/MR systems which…
SurfGNN: A robust surface-based prediction model with interpretability for coactivation maps of spatial and cortical features
Zhuoshuo Li, Jiong Zhang, Youbing Zeng +7
Current brain surface-based prediction models often overlook the variability of regional attributes at the cortical feature level. While graph neural networks (GNNs) excel at captu…