From the 1 of 18 linked papers with an AI index.
12 citations · 12 across the 1 of their papers we have counts for
18 papers
The TopCoW Challenge -- Topology-Aware Circle of Willis Segmentation for CT and MR Angiography
Kaiyuan Yang, Fabio Musio, Yihui Ma +112
The paper introduces the TopCoW Challenge, a benchmark for automatically segmenting the Circle of Willis in CT and MR angiography using deep learning, and provides a new annotated…
A Physics-Guided Neural Framework for Rheology Measurement from Dynamical Laser Speckles
Titanliang Wang, Thomas Goudoulas, Ehsan Fattahi +7
Critical breakthroughs in the area of biomedicine and materials science increasingly depend on rapid, non-contact methods for viscoelastic characterization. Laser Speckle Rheology…
The MICCAI Federated Tumor Segmentation (FeTS) Challenge 2024: Efficient and Robust Aggregation Methods for Federated Learning
Akis Linardos, Sarthak Pati, Ujjwal Baid +25
We present the design and results of the MICCAI Federated Tumor Segmentation (FeTS) Challenge 2024, which focuses on federated learning (FL) for glioma sub-region segmentation in m…
Individualizing Glioma Radiotherapy Planning by Optimization of Data and Physics-Informed Discrete Loss
Michal Balcerak, Jonas Weidner, Petr Karnakov +8
Brain tumor growth is unique to each glioma patient and extends beyond what is visible in imaging scans, infiltrating surrounding brain tissue. Understanding these hidden patient-s…
Efficient Deep Learning-based Forward Solvers for Brain Tumor Growth Models
Zeineb Haouari, Jonas Weidner, Yeray Martin-Ruisanchez +5
Glioblastoma, a highly aggressive brain tumor, poses major challenges due to its poor prognosis and high morbidity rates. Partial differential equation-based models offer promising…
Addressing Annotation Scarcity in Hyperspectral Brain Image Segmentation with Unsupervised Domain Adaptation
Tim Mach, Daniel Rueckert, Alex Berger +2
This work presents a novel deep learning framework for segmenting cerebral vasculature in hyperspectral brain images. We address the critical challenge of severe label scarcity, wh…