A Fast Nonlinear Sparse Model for Blind Image Deblurring. [PDF]
Zhang Z +8 more
europepmc +1 more source
Abstract Background Spatial resolution in preclinical cone‐beam micro‐CT is conventionally characterised by image‐domain metrics measured on a specific reconstruction of a specific phantom. Such metrics conflate resolution loss originating in the data (photon noise, angular undersampling) with resolution loss originating in the reconstruction ...
Falk L. Wiegmann, Nancy L. Ford
wiley +1 more source
Impact of depth-of-interaction and spatially-variant point-spread-function model on the performance of ultra-high resolution brain PET. [PDF]
Zeng T +12 more
europepmc +1 more source
Abstract Background Image noise in digital mammography (DM) can obscure image details and reduce the detectability of clinically relevant findings such as microcalcifications. Purpose To present and evaluate an extended model‐based (MB) image restoration pipeline for DM that incorporates quantum, electronic, and structural noise components, as well as ...
Renann F. Brandão +7 more
wiley +1 more source
MicroDeblurNet: high-fidelity restoration of spatially variant defocus in microscopic images for cucumber downy mildew. [PDF]
Zhang Y +5 more
europepmc +1 more source
A Novel Search Approach for Blur Kernel Estimation of Defocused Image Restoration
AHN, Sangwoo, CHONG, Jongwha
openaire +2 more sources
Evaluating Perfusion Quantification for Phase‐Resolved Functional Lung MRI Using Gaussian Filtering
Current PREFUL perfusion quantification uses a slice‐wise median for the maximal blood exchange fraction ΔS, limiting regional information. Gaussian filtering (σ = 1.5) ΔS in perfusion calculation adds regional information and improves intrascan and interscan repeatability while preserving global and voxel‐wise correlations with DCE‐derived pulmonary ...
Kirsten J. Schmidt +7 more
wiley +1 more source
RulerNet: Learning perspective-invariant ruler representations for robust image scale estimation. [PDF]
Pan Y +5 more
europepmc +1 more source
3dcon: tomogram denoising by deconvolution
An open‐source entropy‐regularized deconvolution workflow is presented for denoising tomographic reconstructions from cryo‐electron microscopy.Cryo‐electron tomography is an expanding technology for the study of macromolecules, viruses and cells.
Peter Kirchweger +3 more
wiley +1 more source
Image Deblurring via Frequency-Domain Feature Enhanced Convolutional Neural Networks. [PDF]
Guo Y, Ma L, Zhang Y.
europepmc +1 more source

