7 citations · 24 across the 17 of their papers we have counts for
19 papers
The Magnetic-Resonance-Based, Omni-Directional Hydrophone
Nathan Thyberg, Davi Cavinatto, Katia Oler +3
This study aims to improve the directional sensitivity of magnetic resonance hydrophone (MRH) methods and allow for detection and quantification of waves traveling at any angle rel…
Can Unsupervised Methods Outperform Supervised Deep Learning When Ground Truth Is Sparse? A Case Study of Bronchovascular Bundle Segmentation in Low-Dose CT
Anna Mrukwa, Marek Socha, Aleksandra Suwalska +9
Background Lung cancer remains the deadliest cancer worldwide because it is often diagnosed too late. Effective treatment depends on detection at an early screening stage. However,…
Light-sheet microscopy to assess cancer pathology: current views and future trends
Uma Pisarović, 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…
Deep Radiomics Detection of Clinically Significant Prostate Cancer on Multicenter MRI: Initial Comparison to PI-RADS Assessment
G. A. Nketiah, M. R. Sunoqrot, E. Sandsmark +5
Objective: To develop and evaluate a deep radiomics model for clinically significant prostate cancer (csPCa, grade group >= 2) detection and compare its performance to Prostate Ima…
Rosette spectroscopic imaging for whole-brain metabolite mapping at 7T: acceleration potential and reproducibility
Zhiwei Huang, Uzay Emir, Andre Doring +4
Whole-brain proton magnetic resonance spectroscopic imaging (1H-MRSI) is a non-invasive technique for assessing neurochemical distribution in the brain, offering valuable insights…
Evaluation of software impact designed for biomedical research: Are we measuring what's meaningful?
Awan Afiaz, Andrey Ivanov, John Chamberlin +24
Software is vital for the advancement of biology and medicine. Analysis of usage and impact metrics can help developers determine user and community engagement, justify additional…
The effects of intra-detector Compton scatter on zero-frequency DQE for photon-counting CT using edge-on-irradiated silicon detectors
Fredrik Grönberg, Zhye Yin, Jonathan Maltz +2
Background: Edge-on-irradiated silicon detectors are currently being investigated for use in photon-counting CT applications. The low atomic number of silicon leads to a significan…
Hessian filter-assisted full diameter at half maximum (FDHM) segmentation and quantification method for optical-resolution photoacoustic microscopy
Dong Zhang, Ran Li, Xin Lou +1
Optical-resolution photoacoustic microscopy has been validated as a high-resolution and high-sensitivity imaging modality for angiographic studies in the past decades. Quantitative…
A Deep Learning Model with Radiomics Analysis Integration for Glioblastoma Post-Resection Survival Prediction
Zongsheng Hu, Zhenyu Yang, Haozhao Zhang +4
Purpose: To develop a novel deep-learning model that integrates radiomics analysis in a multi-dimensional feature fusion workflow for glioblastoma (GBM) post-resection survival pre…
Pressure dependent magnetic properties on bulk CrBr3 single crystals
Rubyann Olmos, Shamsul Alam, Po Hao Chang +6
The van der Waals class of materials offer an approach to two-dimensional magnetism as their spin fluctuations can be tuned upon exfoliation of layers. Moreover, it has recently be…
Frequency shifts in the EPR spectrum of K due to spin-exchange collisions with polarized He and precise He polarimetry
Sumudu Katugampola, Christopher Jantzi, David A. Keder +6
The Zeeman splittings and EPR frequencies of alkali-metal atoms are shifted in the presence of a polarized noble gas. For a spherical geometry, the shift is enhanced over what is e…
Role of AI in Theranostics: Towards Routine Personalized Radiopharmaceutical Therapies
Julia Brosch-Lenz, Fereshteh Yousefirizi, Katherine Zukotynski +5
We highlight emerging uses of artificial intelligence (AI) in the field of theranostics, focusing on its significant potential to enable routine and reliable personalization of rad…
Artifacts of Quantization in Distance Transforms
Bryce A. Besler, Tannis D. Kemp, Nils D. Forkert +1
Distance transforms are a central tool in shape analysis, morphometry, and curve evolution problems. This work describes and investigates an artifact present in distance maps compu…
Optimized application of double and single layer BEM for in vivo conductivity estimation
Jan C de Munck, Andreas Daffertshofer, Victoria Montes-Restrepo +3
Inter subject variability of the electrical conductivity of brain, skull and skin strongly limits the accuracy by which current sources underlying electro-encephalography (EEG) can…