Search Results for author:
Found 8 papers, 2 papers with code
Image quality assessment for closed-loop computer-assisted lung ultrasound
The diagnosis assistance module can then be trained with data that are deemed of sufficient quality, guaranteed by the closed-loop feedback mechanism from the quality assessment module.
The challenges of deploying artificial intelligence models in a rapidly evolving pandemic
The COVID-19 pandemic, caused by the severe acute respiratory syndrome coronavirus 2, emerged into a world being rapidly transformed by artificial intelligence (AI) based on big data, computational power and neural networks.
Reproducibility of an airway tapering measurement in CT with application to bronchiectasis
Purpose: This paper proposes a pipeline to acquire a scalar tapering measurement from the carina to the most distal point of an individual airway visible on CT. We show the applicability of using tapering measurements on clinically acquired data by quantifying the reproducibility of the tapering measure.
Tapering Analysis of Airways with Bronchiectasis
We propose a simple measurement of tapering along the airways to diagnose and monitor bronchiectasis.
Uncertainty in multitask learning: joint representations for probabilistic MR-only radiotherapy planning
Multi-task neural network architectures provide a mechanism that jointly integrates information from distinct sources.
Augmented Reality needle ablation guidance tool for Irreversible Electroporation in the pancreas
Irreversible electroporation (IRE) is a soft tissue ablation technique suitable for treatment of inoperable tumours in the pancreas.
Computer-assisted polyp matching between optical colonoscopy and CT colonography: a phantom study
Furthermore, we evaluate the matching of the reconstructed polyp from OC with other colonic endoluminal surface structures such as haustral folds and show that there is a minimum at the correct polyp from CTC.
Numerical Methods for Coupled Reconstruction and Registration in Digital Breast Tomosynthesis
We evaluate our methods using various computational digital phantoms, uncompressed breast MR images, and in-vivo DBT simulations.
