Optimal design for multi-compartment cell elasticity estimation using AFM and super-resolution imaging.

Continuous image representation based on deep learning for reducing interpolation bias in DIC

Lightweight image super resolution method inspired by memory consolidation mechanism

Edge priors guided deep unrolling network for single image super-resolution

Material proportion guided hyperspectral image super-resolution via unmixing

Global vision in lightness: A novel approach to lightweight image super-resolution using global feature distillation

Industrial visual defect detection oriented context-modulated and cross-layer interaction network for image super-resolution

Memory-Driven Wavelet Network for lightweight infrared image super-resolution

Local-global context-aware and structure-preserving image super-resolution

UFAT: Unified feature-aware transformer with holistic attention modeling for image super-resolution

Global and local Mamba network for multi-modality medical image super-resolution

LU-mamba: LiDAR upsampling via bidirectional state space modeling on range images.

One-step diffusion-based real-world image super-resolution with visual perception distillation

Advanced secure and seismic-resilient data transmission in MANET-IoT using dual transformer based super resolution networks and polymorphic cryptography

Algorithm-hardware co-design of binary neural network for efficient super resolution on FPGA

Deep learning reconstruction (DLR) algorithms have begun replacing iterative reconstruction (IR) in CT. Besides the potential to reduce noise, the application of artificial intelligence can also allow for "super resolution," allowing traditional CT systems to produce images with improved spatial resolution by training against higher-resolution images. This study aims to characterize the image quality produced by a DLR "super resolution" algorithm. This study compares Canon's Precise IQ Engine (PIQE) Cardiac, a DLR algorithm, with the AIDR Enhanced 3D iterative reconstruction (IR) algorithm using quantitative phantom-based image quality measurements. Scans of the American College of Radiology (ACR) Gammex 464 image quality phantom with and without a torso-sized elliptical ring were acquired using CTDIvol of 2.6, 15.7, and 32.9 mGy. Each experimental condition was scanned 20 times. Reconstructions used AIDR with a cardiac kernel and PIQE Cardiac with both 512×512 and 1024×1024 matrices. The task-based modulation transfer function (MTFtask) was calculated for Teflon, acrylic, polyethylene, and air inserts. Contrast-to-noise ratio (CNR) and low-contrast object specific CNR (CNRLO) were calculated for the 25-mm and 6-mm low-contrast disks in module 2 of the phantom. NPS and noise magnitude were calculated from the module's background. Both versions of PIQE showed improvement in MTFtask over AIDR for most frequencies, with PIQE 1024 outperforming PIQE 512. Larger differences were noted at higher contrast levels and with the smaller phantom. NPS curves for PIQE 512 and PIQE 1024 were nearly identical at all doses. AIDR showed a noise magnitude at least 44% higher than PIQE for all scenarios. The NPS shapes differed between AIDR and PIQE, producing noticeably different noise textures that were dose- and phantom size-dependent. CNRLO values were similar between PIQE 512 and PIQE 1024 and were higher than those of AIDR for most scenarios; however, AIDR outperformed PIQE for the 6-mm objects at the medium and high doses. Use of PIQE on the 25-mm disk permits dose reductions in the small phantom without loss of CNRLO. PIQE provides substantial image quality improvements over AIDR in phantom-based quantitative measurements. The potential for dose reduction is also noted. PIQE 1024 can be used to improve the spatial resolution over PIQE 512, with no apparent trade-offs in image quality.

We present a new hybrid 3D scaffold, fabricated via MultiPhoton Lithography (MPL), that integrates synthetic polymers (BisSR/CEA) with methacrylated collagen type I (Coll-MA) and enables geometry-dependent single-cell confinement in most cages, while allowing cell-cell contact when the scaffold design permits multiple occupancy. We showcase that nanoscale structures with feature sizes down to hundreds of nanometers and locally tunable mechanical properties (kPa to MPa) can be achieved. Scaffold bioactivity is confirmed using 3D Single-Molecule Localization Microscopy (SMLM). We quantified the dynamic 3D behavior of vinculin through its mechanoresponsive nanoscale localization. Notably, vinculin dynamics was independent of scaffold composition, including geometry, mechanical properties, and biodegradability. In contrast, collagen I and osteocalcin expression levels were strongly elevated in cells confined by hybrid scaffolds, indicating that scaffold bioactivity and geometry, rather than stiffness, govern stem cell fate. Our platform combines precisely tunable micro- and nanoscale environments mimicking extracellular matrix (ECM) features with super-resolution imaging. This 3D tissue scaffold is component compatible with subsequent Organ-on-a-Chip chamber integration and supports physiologically relevant bone tissue models.

We generated a comparative spatial proteomic atlas of the human and mouse retina using a highly multiplexed immunohistochemistry technique called iterative bleaching extends multiplexity (IBEX). We refined the IBEX workflow by integrating an antibody dissociation option alongside chemical bleaching. This dual strategy enabled removal of the entire antibody complex, permitting the flexible use of antibodies from the same host species across iterative cycles. We coupled this workflow with super-resolution imaging via deconvolution and applied it to the retina of healthy humans and WT mice and the Crb1rd8 mouse model. We successfully imaged over 25 protein markers on human and mouse tissue sections, generating spatial atlases of the major retinal cell populations. Cross-species protein expression was compared to scRNA-seq datasets to identify protein and transcript disparities. Super-resolution IBEX delineated the ultrastructural features of the outer limiting membrane (OLM), identifying CD44 as a core structural component tightly colocalized with a highly organized F-actin belt within Müller glial endfeet. Using the Crb1rd8 mouse model, disruption of this complex was spatially associated with rosette formation and OLM structural failure. In summary, spatial proteomic atlases of the human and mouse retina were used to reveal insights into the arrangement of major retinal cell populations and OLM structure.

Receptor tyrosine kinase signaling is initiated by extracellular ligand binding, which drives the formation of membrane-protein assemblies that activate intracellular signal transduction. Accurately resolving the molecular composition of these assemblies in situ remains challenging due to their nanoscale dimensions and intrinsic heterogeneity. Here, we introduce a single-molecule super-resolution imaging and analysis workflow designed to resolve and quantitatively characterize individual membrane-protein assembly sites in cells. We apply this approach to the nanoscale organization of the epidermal growth factor receptor (EGFR) and its adaptor protein Grb2 following stimulation with the native ligand epidermal growth factor. As activation progresses, we observe a reduction in EGFR density at the plasma membrane, a progressive accumulation of Grb2 at EGFR assembly sites, and an increase in both dimeric and higher-order oligomeric EGFR. The experimental and analytical framework presented here is broadly applicable to the study of diverse membrane-protein assemblies.

Reversibly switchable fluorescent proteins (RSFPs) transition many times between dark and fluorescent states under minimal light doses. The photoswitching can happen at different speed, contrast and length, and it is often challenging for users to select the optimal imaging scheme to generate images with high contrast and spatial resolution. Here, we experimentally investigate the photophysical properties of different RSFPs under imaging conditions, together with an in silico exploration of their role in nanoscale image formation. We developed open-source software that uses measured parameters such as brightness, switching speed, photoswitching fatigue, labelling densities, noise and illumination type to generate the related RESOLFT (reversible saturable/switchable optical fluorescence transition) super-resolution image. This tool can be used to select optimal imaging schemes for known RSFPs and to guide the rational development of new proteins.