Automated construction of surface geometries of cardiac structures from volumetric medical images is important for a number of clinical applications. While deep-learning-based approaches have demonstrated promising reconstruction precision, these app...
Although deep learning networks applied to digital images have shown impressive results for many pathology-related tasks, their black-box approach and limitation in terms of interpretability are significant obstacles for their widespread clinical uti...
The rapid economic and social development has led to a rapid increase in the output of domestic waste. How to realize waste classification through intelligent methods has become a key factor for human beings to achieve sustainable development. Tradit...
Fourier transform infrared (FTIR) spectroscopy combined with backpropagation artificial neural network (BP-ANN) were utilized for rapid and simultaneous assessment of the lipid oxidation indices in French fries. The conventional indexes (i.e. total p...
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Sep 8, 2021
Relatively abundant availability of medical imaging data has provided significant support in the development and testing of Neural Network based image processing methods. Clinicians often face issues in selecting suitable image processing algorithm f...
European journal of cancer (Oxford, England : 1990)
Sep 8, 2021
BACKGROUND: Multiple studies have compared the performance of artificial intelligence (AI)-based models for automated skin cancer classification to human experts, thus setting the cornerstone for a successful translation of AI-based tools into clinic...
Exploiting photoplethysmography signals (PPG) for non-invasive blood pressure (BP) measurement is interesting for various reasons. First, PPG can easily be measured using fingerclip sensors. Second, camera based approaches allow to derive remote PPG ...
Neuromorphic hardware systems have been gaining ever-increasing focus in many embedded applications as they use a brain-inspired, energy-efficient spiking neural network (SNN) model that closely mimics the human cortex mechanism by communicating and ...
The presence of computation and transmission-variable time delays within a robotic control loop is a major cause of instability, hindering safe human-robot interaction (HRI) under these circumstances. Classical control theory has been adapted to coun...
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