The image fusion methods based on deep learning has become a research hotspot in the
field of computer vision in recent years. This paper reviews these methods from five aspects …

The structure and function of dietary proteins, as well as their subcellular prediction, are
critical for designing and developing new drug compositions and understanding the …

Utilizing multi-modal neuroimaging data is proven to be effective in investigating human
cognitive activities and certain pathologies. However, it is not practical to obtain the full set of …

Refined and automatic retinal vessel segmentation is crucial for computer-aided early
diagnosis of retinopathy. However, existing methods often suffer from mis-segmentation …

Hyperspectral image (HSI) and light detection and ranging (LiDAR) data fusion have been
widely employed in HSI classification to promote interpreting performance. In the existing …

We investigate two neuro-developmental disorders in children–Autism Spectrum Disorder
(ASD) and Attention-deficit/hyperactivity disorder (ADHD). Most works in literature have …

Medical image fusion technology integrates the contents of medical images of different
modalities, thereby assisting users of medical images to better understand their meaning …

Multi-modality imaging improves disease diagnosis and reveals distinct deviations in tissues
with anatomical properties. The existence of completely aligned and paired multi-modality …

Glioma grading during surgery can help clinical treatment planning and prognosis, but
intraoperative pathological examination of frozen sections is limited by the long processing …

Sepsis is a life-threatening medical condition that is characterized by the dysregulated
immune system response to infections, having both high morbidity and mortality rates. Early …