AIMC Topic: Image Processing, Computer-Assisted

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The optimisation of deep neural networks for segmenting multiple knee joint tissues from MRIs.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Automated semantic segmentation of multiple knee joint tissues is desirable to allow faster and more reliable analysis of large datasets and to enable further downstream processing e.g. automated diagnosis. In this work, we evaluate the use of condit...

Unravelling the effect of data augmentation transformations in polyp segmentation.

International journal of computer assisted radiology and surgery
PURPOSE: Data augmentation is a common technique to overcome the lack of large annotated databases, a usual situation when applying deep learning to medical imaging problems. Nevertheless, there is no consensus on which transformations to apply for a...

Bone age assessment based on deep convolution neural network incorporated with segmentation.

International journal of computer assisted radiology and surgery
PURPOSE: Bone age assessment is not only an important means of assessing maturity of adolescents, but also plays an indispensable role in the fields of orthodontics, kinematics, pediatrics, forensic science, etc. Most studies, however, do not take in...

3D Deep Neural Network Segmentation of Intracerebral Hemorrhage: Development and Validation for Clinical Trials.

Neuroinformatics
Intracranial hemorrhage (ICH) occurs when a blood vessel ruptures in the brain. This leads to significant morbidity and mortality, the likelihood of which is predicated on the size of the bleeding event. X-ray computed tomography (CT) scans allow cli...

THEIA™ development, and testing of artificial intelligence-based primary triage of diabetic retinopathy screening images in New Zealand.

Diabetic medicine : a journal of the British Diabetic Association
AIM: To develop and evaluate an artificial intelligence triage system with high sensitivity for detecting referable diabetic retinopathy and maculopathy, while maintaining high specificity for non-referable disease, for clinical implementation within...

Lower dimensional kernels for video discriminators.

Neural networks : the official journal of the International Neural Network Society
This work presents an analysis of the discriminators used in Generative Adversarial Networks (GANs) for Video. We show that unconstrained video discriminator architectures induce a loss surface with high curvature which make optimization difficult. W...

Deep neural network models for computational histopathology: A survey.

Medical image analysis
Histopathological images contain rich phenotypic information that can be used to monitor underlying mechanisms contributing to disease progression and patient survival outcomes. Recently, deep learning has become the mainstream methodological choice ...

High-performance rapid MR parameter mapping using model-based deep adversarial learning.

Magnetic resonance imaging
PURPOSE: To develop and evaluate a deep adversarial learning-based image reconstruction approach for rapid and efficient MR parameter mapping.

Truncation compensation and metallic dental implant artefact reduction in PET/MRI attenuation correction using deep learning-based object completion.

Physics in medicine and biology
The susceptibility of MRI to metallic objects leads to void MR signal and missing information around metallic implants. In addition, body truncation occurs in MR imaging for large patients who exceed the transaxial field-of-view of the scanner. Body ...