57 citations · 58 across the 4 of their papers we have counts for
6 papers
Comprehensive Multimodal Deep Learning Survival Prediction Enabled by a Transformer Architecture: A Multicenter Study in Glioblastoma
Ahmed Gomaa, Yixing Huang, Amr Hagag +16
Background: This research aims to improve glioblastoma survival prediction by integrating MR images, clinical and molecular-pathologic data in a transformer-based deep learning mod…
Risk Classification of Brain Metastases via Radiomics, Delta-Radiomics and Machine Learning
Philipp Sommer, Yixing Huang, Christoph Bert +5
Stereotactic radiotherapy (SRT) is one of the most important treatment for patients with brain metastases (BM). Conventionally, following SRT patients are monitored by serial imagi…
snapshot CEST++ : the next snapshot CEST for fast whole-brain APTw imaging at 3T
Patrick Liebig, Maria Sedykh, Kai Herz +6
CEST suffers from two main problems long acquisitin times or restricted coverage as well as incoherent protocol settings. In this paper we give suggestions on how to optimise your…
Deep learning for brain metastasis detection and segmentation in longitudinal MRI data
Yixing Huang, Christoph Bert, Philipp Sommer +10
Brain metastases occur frequently in patients with metastatic cancer. Early and accurate detection of brain metastases is very essential for treatment planning and prognosis in rad…
MR to X-Ray Projection Image Synthesis
Bernhard Stimpel, Christopher Syben, Tobias Würfl +3
Hybrid imaging promises large potential in medical imaging applications. To fully utilize the possibilities of corresponding information from different modalities, the information…
Precision Learning: Reconstruction Filter Kernel Discretization
Christopher Syben, Bernhard Stimpel, Katharina Breininger +4
In this paper, we present substantial evidence that a deep neural network will intrinsically learn the appropriate way to discretize the ideal continuous reconstruction filter. Cur…