Multimodal medical image fusion consists in combining two or more images of the same or
different modalities aiming to improve the image content, and preserve information. The …

The images captured by the cameras contain distortions, misclassified pixels, uncertainties
and poor contrast. Therefore, the multi-focus image fusion (MFIF) integrates various input …

Medical image fusion is a relevant area with widespread application in disease diagnosis
and prediction with easily available image scans of Computed Tomography, Positron …

Dynamic threshold neural P systems (DTNP systems) are a distributed parallel computing
model with an interesting mechanism involving the cooperative spiking of neurons in a local …

Multi-modal medical image fusion brings many benefits to clinical diagnosis and analysis
because it creates favorable conditions for diagnostic imaging practitioners to make a more …

Coupled neural P (CNP) systems are a recently developed Turing-universal, distributed and
parallel computing model, combining the spiking and coupled mechanisms of neurons. This …

Medical image fusion is a technique of extracting information from multiple image modalities
and combining them to create a single image with the aim of improving the image content …

Coupled neural P (CNP) systems are recently developed distributed and parallel computing
models that are abstracted by the mechanisms of coupled and spiking neurons. CNP …

Multimodality medical image fusion is the process of combining multiple images from single
or multiple modalities of imaging. Medical image fusion methods are adopted to increase the …

Dynamic threshold neural P systems (DTNP systems) are recently proposed distributed and
parallel computing models, inspired from the intersecting cortical model. DTNP systems …