Brief review of image denoising techniques

L Fan, F Zhang, H Fan, C Zhang - Visual Computing for Industry …, 2019 - Springer
With the explosion in the number of digital images taken every day, the demand for more
accurate and visually pleasing images is increasing. However, the images captured by …

Deep learning for brain MRI segmentation: state of the art and future directions

Z Akkus, A Galimzianova, A Hoogi, DL Rubin… - Journal of digital …, 2017 - Springer
Quantitative analysis of brain MRI is routine for many neurological diseases and conditions
and relies on accurate segmentation of structures of interest. Deep learning-based …

Image denoising review: From classical to state-of-the-art approaches

B Goyal, A Dogra, S Agrawal, BS Sohi, A Sharma - Information fusion, 2020 - Elsevier
At the crossing of the statistical and functional analysis, there exists a relentless quest for an
efficient image denoising algorithm. In terms of greyscale imaging, a plethora of denoising …

Deep gaussian scale mixture prior for spectral compressive imaging

T Huang, W Dong, X Yuan, J Wu… - Proceedings of the …, 2021 - openaccess.thecvf.com
In coded aperture snapshot spectral imaging (CASSI) system, the real-world hyperspectral
image (HSI) can be reconstructed from the captured compressive image in a snapshot …

Deep learning for image enhancement and correction in magnetic resonance imaging—state-of-the-art and challenges

Z Chen, K Pawar, M Ekanayake, C Pain, S Zhong… - Journal of Digital …, 2023 - Springer
Magnetic resonance imaging (MRI) provides excellent soft-tissue contrast for clinical
diagnoses and research which underpin many recent breakthroughs in medicine and …

volBrain: an online MRI brain volumetry system

JV Manjón, P Coupé - Frontiers in neuroinformatics, 2016 - frontiersin.org
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 …

MRI segmentation and classification of human brain using deep learning for diagnosis of Alzheimer's disease: a survey

N Yamanakkanavar, JY Choi, B Lee - Sensors, 2020 - mdpi.com
Many neurological diseases and delineating pathological regions have been analyzed, and
the anatomical structure of the brain researched with the aid of magnetic resonance imaging …

Bassoon contributes to tau-seed propagation and neurotoxicity

P Martinez, H Patel, Y You, N Jury, A Perkins… - Nature …, 2022 - nature.com
Tau aggregation is a defining histopathological feature of Alzheimer's disease and other
tauopathies. However, the cellular mechanisms involved in tau propagation remain unclear …

Cortical thickness and central surface estimation

R Dahnke, RA Yotter, C Gaser - Neuroimage, 2013 - Elsevier
Several properties of the human brain cortex, eg, cortical thickness and gyrification, have
been found to correlate with the progress of neuropsychiatric disorders. The relationship …

Nonlocal transform-domain filter for volumetric data denoising and reconstruction

M Maggioni, V Katkovnik… - IEEE transactions on …, 2012 - ieeexplore.ieee.org
We present an extension of the BM3D filter to volumetric data. The proposed algorithm,
BM4D, implements the grouping and collaborative filtering paradigm, where mutually similar …