Over the past two decades, medical imaging and diagnostic techniques have gained
immense attraction due to the rapid development in computing, internet, data storage and …

Diffusion MRI (dMRI) provides invaluable information for the study of tissue microstructure
and brain connectivity, but suffers from a range of imaging artifacts that greatly challenge the …

We introduce and evaluate a post-processing technique for fast denoising of diffusion-
weighted MR images. By exploiting the intrinsic redundancy in diffusion MRI using universal …

A large range of sophisticated brain image analysis tools have been developed by the
neuroscience community, greatly advancing the field of human brain mapping. Here we …

Hyperspectral image (HSI) denoising plays an important role in image quality improvement
and related applications. Convolutional neural network (CNN)-based image denoising …

Accurate segmentation of different sub-regions of gliomas such as peritumoral edema,
necrotic core, enhancing, and non-enhancing tumor core from multimodal MRI scans has …

The amount of medical image data produced in clinical and research settings is rapidly
growing resulting in vast amount of data to analyze. Automatic and reliable quantitative …

Image denoising—removal of additive white Gaussian noise from an image—is one of the
oldest and most studied problems in image processing. Extensive work over several …

Brain tumor segmentation aims to separate the different tumor tissues such as active cells,
necrotic core, and edema from normal brain tissues of White Matter (WM), Gray Matter (GM) …

In a small fraction of patients with schizophrenia or autism, alleles of copy-number variants
(CNVs) in their genomes are probably the strongest factors contributing to the pathogenesis …