Locally Rotation Invariant (LRI) image analysis was shown to be fundamental in many applications and in particular in medical imaging where local structures of tissues occur at arbitrary rotations. LRI constituted the cornerstone of several breakthro...
Photodiagnosis and photodynamic therapy
Jun 17, 2020
• Severe lung complications can be explored using computed tomography during COVID-19 pandemic. • Ultra-low dose CT can enhance COVID-19 infected patients diagnostic capability. • Optically monitored CT along with deep learning is the best solution f...
Deep learning explainability is often reached by gradient-based approaches that attribute the network output to perturbations of the input pixels. However, the relevance of input pixels may be difficult to relate to relevant image features in some ap...
INTRODUCTION: Artificial intelligence (AI) describes the use of computational techniques to mimic human intelligence. In healthcare, this typically involves large medical datasets being used to predict a diagnosis, identify new disease genotypes or p...
In the present article, we provide an overview on the basics of deep learning in terms of technical aspects and steps required to launch a deep learning research. Deep learning is a branch of artificial intelligence, which has been attracting interes...
Biomedical physics & engineering express
Jun 12, 2020
The use of intra-operative imaging system as an intervention solution to provide more accurate localization of complicated structures has become a necessity during the neurosurgery. However, due to the limitations of conventional imaging systems, hig...
The next generation of intelligent robotic systems has been envisioned as micro-scale mobile and externally controllable robots. Visualization of such small size microrobots to track their motion in nontransparent medium such as human tissue remains ...
Pulse-coupled neural network (PCNN) and its modified models are suitable for dealing with multi-focus and medical image fusion tasks. Unfortunately, PCNNs are difficult to directly apply to multispectral image fusion, especially when the spectral fid...
BACKGROUND: Photographic diabetic retinopathy screening requires labour-intensive grading of retinal images by humans. Automated retinal image analysis software (ARIAS) could provide an alternative to human grading. We compare the performance of an A...
Machine learning (ML) and deep learning (DL) systems, currently employed in medical image analysis, are data-driven models often considered as black boxes. However, improved transparency is needed to translate automated decision-making to clinical pr...
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