Article
Biotechnology & Applied Microbiology
Weisong Zhao, Shiqun Zhao, Liuju Li, Xiaoshuai Huang, Shijia Xing, Yulin Zhang, Guohua Qiu, Zhenqian Han, Yingxu Shang, De-En Sun, Chunyan Shan, Runlong Wu, Lusheng Gu, Shuwen Zhang, Riwang Chen, Jian Xiao, Yanquan Mo, Jianyong Wang, Wei Ji, Xing Chen, Baoquan Ding, Yanmei Liu, Heng Mao, Bao-Liang Song, Jiubin Tan, Jian Liu, Haoyu Li, Liangyi Chen
Summary: Sparse structured illumination microscopy (Sparse-SIM) achieves nearly twofold resolution enhancement by utilizing sparse deconvolution algorithm, enabling the resolution of intricate biological structures such as small fusion pores, nuclear pores, and relative movements of inner and outer mitochondrial membranes.
NATURE BIOTECHNOLOGY
(2022)
Article
Optics
Xin Tian, Ying Xiao, Rui Liu, Fang He, Jiayi He
Summary: This Letter presents a novel line-wise scanning-based super-resolution (LSSR) imaging method that uses line-based optical multiplexing to capture low-resolution images and a joint reconstruction algorithm to generate high-resolution images. The method efficiently suppresses stripe noises and shows significant advantages in visual quality and quantitative measurement compared to other state-of-the-art methods.
Article
Computer Science, Artificial Intelligence
Yanyang Yan, Wenqi Ren, Xiaobin Hu, Kun Li, Haifeng Shen, Xiaochun Cao
Summary: This paper proposes a novel single image Super-Resolution network based on Graph ATtention network (SRGAT) to fully utilize the internal patch-recurrence in natural images. By considering the internal patch-recurrence of an image through constructing a graph network, the proposed model uses graph attention network to interact with neighboring patches and recover additional textures, complementing texture details learned from the content branch. Extensive evaluations demonstrate that the proposed algorithm outperforms state-of-the-art super-resolution methods.
IEEE TRANSACTIONS ON IMAGE PROCESSING
(2021)
Article
Radiology, Nuclear Medicine & Medical Imaging
Yasunori Nagayama, Takafumi Emoto, Yuki Kato, Masafumi Kidoh, Seitaro Oda, Daisuke Sakabe, Yoshinori Funama, Takeshi Nakaura, Hidetaka Hayashi, Sentaro Takada, Ryutaro Uchimura, Masahiro Hatemura, Kenichi Tsujita, Toshinori Hirai
Summary: This study evaluated the effect of super-resolution deep-learning-based reconstruction (SR-DLR) on the image quality of coronary CT angiography (CCTA). The results showed that SR-DLR significantly improved image quality, noise, and contrast-to-noise ratio (CNR) compared to other reconstruction algorithms. In addition, SR-DLR also improved object detectability in CCTA.
EUROPEAN RADIOLOGY
(2023)
Article
Computer Science, Artificial Intelligence
Yuming Jiang, Kelvin C. K. Chan, Xintao Wang, Chen Change Loy, Ziwei Liu
Summary: Reference-based Super-Resolution (Ref-SR) is a promising approach to enhance low-resolution images by using high-resolution reference images. In this work, we propose C-2-Matching to address the transformation and resolution gaps between input and reference images. By contrastive correspondence matching and teacher-student correlation distillation, we bridge the transformation and resolution gaps. We also design a dynamic aggregation module to handle potential misalignment issues.
IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
(2023)
Article
Engineering, Electrical & Electronic
Matthew Aquilina, Christian Galea, John Abela, Kenneth P. Camilleri, Reuben A. Farrugia
Summary: Convolutional Neural Networks have shown impressive performance in super-resolution and image restoration tasks, but accurately super-resolving images with multiple degradations can still be challenging. Previous attempts to inform SR networks with degradation parameters have shown improvements, but often require significant architectural changes. This letter introduces meta-attention as a simple mechanism to improve the accuracy of SR networks with relevant degradation metadata.
IEEE SIGNAL PROCESSING LETTERS
(2021)
Article
Computer Science, Information Systems
Tiesong Zhao, Yuting Lin, Yiwen Xu, Weiling Chen, Zhou Wang
Summary: This study introduces a method for image super-resolution quality assessment using a large-scale database and deep learning models. A SISAR database was constructed with a novel semi-automatic labeling approach, and a DISQ model was used for quality prediction, demonstrating promising performance in cross-database tests. The SISAR database and DISQ model will be publicly available for reproducible research.
IEEE TRANSACTIONS ON MULTIMEDIA
(2021)
Article
Computer Science, Information Systems
Yanming Ye, Mengxiong Zhou, Zhanyu Wang, Xingfa Shen
Summary: This paper proposes a divide-and-conquer strategy to synthesize a high-resolution depth image from a low-resolution range image under the guidance of a registered high-resolution color image. Different interpolation methods are used for planar areas and edge regions, and the upsampling results are refined using a Depth CNN. Experimental results demonstrate that our method achieves the best quality with fewer artifacts compared to classical super-resolution algorithms, and our depth CNN outperforms state-of-the-art methods in qualitative and quantitative evaluations.
Article
Computer Science, Artificial Intelligence
Qing Cai, Yiming Qian, Jinxing Li, Jun Lyu, Yee-Hong Yang, Feng Wu, David Zhang
Summary: This paper presents a new Transformer architecture called HIPA, which progressively recovers high-resolution images using hierarchical patch partitioning. It also proposes an attention-based position encoding scheme and a multi-receptive field attention module. Experimental results demonstrate the superior performance of HIPA over previous methods in both quantitative and qualitative aspects.
IEEE TRANSACTIONS ON IMAGE PROCESSING
(2023)
Article
Computer Science, Information Systems
Zikang Wei, Yunqing Liu
Summary: With the improvement of satellite remote sensing technology, the development of super-resolution image reconstruction technology has been promoted, and a GAN image super-resolution reconstruction model based on cavity residues in dense connection blocks has been constructed. The introduction of cloud computing service model has improved the performance of the image reconstruction system, bringing great economic benefits.
COMPUTER COMMUNICATIONS
(2021)
Article
Geochemistry & Geophysics
Jiangsan Zhao, Ying Qu, Seishi Ninomiya, Wei Guo
Summary: This paper proposes an unsupervised learning method to prevent the performance degradation of HSI-SR models by learning the camera response function (CRF). By decomposing RGB images and optimizing the linear CRF learning network, the successfully learned CRF can effectively prevent performance drop.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2022)
Article
Computer Science, Information Systems
Shenghang Zhou, Xiubao Sui, Hao Xie, Qian Chen, Guohua Gu
Summary: A method to construct a large transmission matrix (TM) of highly scattering media based on an algorithm is presented. By defining and constructing a large TM from several naturally measured complementary small TMs using a multiframe image super-resolution algorithm, high-resolution (HR) image reconstruction is achieved. Optical experiments have proven the feasibility of the proposed method in improving existing TM-based image reconstruction applications and offering new perspectives on the size of TM measurements and imaging resolution.
Article
Computer Science, Hardware & Architecture
Jingwen Zuo, Zhen Wang, Yang Zhang, Zhouquan Yan, Yali Zhao, Yuantao Chen
Summary: The paper introduces an improved image super-resolution algorithm based on mixed deep convolutional networks, which conducts feature extraction and reconstruction on low-resolution images, and experiments on several datasets show improvements in Peak Signal-to-Noise Ratio and Structural Similarity.
COMPUTERS & ELECTRICAL ENGINEERING
(2021)
Article
Engineering, Electrical & Electronic
Pasquale Cascarano, Luca Calatroni, Elena Loli Piccolomini
Summary: This study proposes a variational model for single-image super-resolution based on the assumption of sparse gradient of the target image, enforcing it with both isotropic and anisotropic l(0) regularisation and quadratic data fidelity. A novel efficient ADMM-splitting algorithm is introduced for numerical realization of the model, with substeps solutions computed efficiently through hard-thresholding and standard conjugate gradient solvers.
IEEE TRANSACTIONS ON COMPUTATIONAL IMAGING
(2021)
Article
Optics
Uri Rossman, Tali Dadosh, Yonina C. Eldar, Dan Oron
Summary: A new analysis approach based on the SPARCOM method was proposed, and experimental results showed that confocal SPARCOM provides higher resolution compared to pixel-reassigned based analysis. This method is expected to enhance the effectiveness of ISM.
Review
Spectroscopy
Carla Harkin, Karl W. Smith, Faye L. Cruickshank, C. Logan Mackay, Bryn Flinders, Ron M. A. Heeren, Tara Moore, Simon Brockbank, Diego F. Cobice
Summary: Mass spectrometry imaging (MSI) combines molecular and spatial information, making it a valuable tool in various applications. Chemical derivatization (CD) has proven to be an effective solution for ionization issues. On-tissue chemical derivatization (OTCD) is a powerful tool for studying the spatial distribution of poorly ionizable molecules within tissues.
MASS SPECTROMETRY REVIEWS
(2022)
Article
Biochemical Research Methods
Anjusha Mathew, Gert B. Eijkel, Ian G. M. Anthony, Shane R. Ellis, Ron M. A. Heeren
Summary: This study used a Timepix detector to investigate the effect of MCP performance on MMA ions generated by nMS, analyzing the dependency of MCP response on various factors and extending the mass and ion characteristics range, resulting in a MCP performance equation based on ion properties.
JOURNAL OF MASS SPECTROMETRY
(2022)
Article
Chemistry, Multidisciplinary
Rald V. M. Groven, Sylvia P. Nauta, Jane Gruisen, Britt S. R. Claes, Johannes Greven, Martijn van Griensven, Martijn Poeze, Ron M. A. Heeren, Tiffany Porta Siegel, Berta Cillero-Pastor, Taco J. Blokhuis
Summary: This study developed a protocol for lipid analysis in fracture hematoma using MALDI-MSI, revealing time-dependent lipid patterns within the fracture hematoma which may serve as a future diagnostic tool. Further research is warranted to explore the clinical implications of this lipid analysis in fracture treatment.
FRONTIERS IN CHEMISTRY
(2022)
Article
Chemistry, Analytical
Aljoscha Korber, Joel D. Keelor, Britt S. R. Claes, Ron M. A. Heeren, Ian G. M. Anthony
Summary: In this study, a new method called fast mass microscopy is proposed, which combines a Timepix3 detector with continuously sampling secondary ion mass spectrometry mass microscope to achieve high throughput imaging at lower mass resolution compared to conventional MSI. This method enables the acquisition of submicron, gigapixel images of fingerprints and rat tissue at significantly faster speeds than traditional microprobe-mode MSI.
ANALYTICAL CHEMISTRY
(2022)
Article
Chemistry, Analytical
Britt S. R. Claes, Kasper K. Krestensen, Gargey Yagnik, Andrej Grgic, Christel Kuik, Mark J. Lim, Kenneth J. Rothschild, Michiel Vandenbosch, Ron M. A. Heeren
Summary: A novel technology called MALDIIHC was published, which combined MALDI-MSI and IHC to achieve targeted imaging of biomolecules in tissue. The utility of targeted MALDIIHC and its complementarity with untargeted on-tissue proteomics was explored using breast cancer tissue. MALDI-2 was also investigated and demonstrated to improve MALDI-IHC. The combination of multiplexed MALDI-IHC with image-guided proteomics showed great potential in studying diseases.
ANALYTICAL CHEMISTRY
(2023)
Article
Chemistry, Analytical
Anjusha Mathew, Joel D. Keelor, Gert B. Eijkel, Ian G. M. Anthony, Jingming Long, Jord Prangsma, Ron M. A. Heeren, Shane R. Ellis
Summary: This study presents the coupling of the TPX3 chip with a TOF MS system, resulting in improved time resolution and extended m/z detection range for ions. The additional information provided by TPX3 enhances the quality of mass spectrum in terms of signal-to-noise ratio. Furthermore, the imaging capabilities of TPX3 allow for spatial and temporal separation of neutral fragments.
ANALYTICAL CHEMISTRY
(2022)
Article
Biochemical Research Methods
Kasper Krijnen, Joel D. Keelor, Sebastian Boehm, Shane R. Ellis, Claus Koester, Jens Hoehndorf, Ron M. A. Heeren, Ian G. M. Anthony
Summary: Mass spectrometry imaging (MSI) is a surface analysis technique used for biological research, and multimodal imaging combining multiple imaging modes can provide a more comprehensive view of samples. In this study, a prototype Bruker timsTOF fleX instrument was modified to include secondary ion mass spectrometry (SIMS) and secondary electron (SE) imaging capabilities while preserving matrix-assisted laser desorption/ionization (MALDI) capability. The modified instrument showed improved efficiency in multimodal imaging, allowing for easy registration of images and eliminating the need for sample transfer.
JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY
(2023)
Article
Multidisciplinary Sciences
Andrej Grgic, Kasper K. Krestensen, Ron M. A. Heeren
Summary: Glycans play diverse roles in biology, and variations in N-glycosylation state within tissues have clinical diagnostic value. A protocol for MALDI MSI of N-glycans from fresh frozen tissue was developed, matching the current standard of FFPE analysis. This protocol significantly improves signal intensity and spatial resolution, enhancing the clinical application of MALDI MSI for N-glycan analysis.
SCIENTIFIC REPORTS
(2023)
Article
Biochemical Research Methods
Britt S. R. Claes, Andrew P. Bowman, Berwyck L. J. Poad, Ron M. A. Heeren, Stephen J. Blanksby, Shane R. Ellis
Summary: The biological functions of lipids highly depend on their molecular structures, specifically even small changes in structure such as different positions of unsaturation serve as critical indicators for changes in metabolism. However, conventional mass spectrometry imaging faces challenges in differentiating lipid isomers with mixture and structural complexity. Recent advances in ozone-induced dissociation coupled with matrix-assisted laser desorption/ionization have shown potential in mapping individual double-bond isomers and visualizing lipid desaturation in adjacent tissue types. This study employs a high-speed gas-phase reaction between ionized lipids and ozone to interrogate anionic glycerophospholipids isomers in biological tissues, providing valuable information on unsaturation and acyl chain composition from a single mass spectrum.
JOURNAL OF THE AMERICAN SOCIETY FOR MASS SPECTROMETRY
(2023)
Article
Polymer Science
Lidia Molina-Millan, Aljoscha Koerber, Bryn Flinders, Berta Cillero-Pastor, Eva Cuypers, Ron M. A. Heeren
Summary: Synthetic polymers, when improperly disposed of, accumulate in the environment and pose potential health risks by degrading into micro- and nanoparticles (MNPs). Matrix-assisted laser desorption/ionization mass spectrometry imaging (MALDI MSI) can be used to study biological or toxicological changes in organisms exposed to MNPs. MALDI-2 has been found to enhance the sensitivity of polymer analysis, making it a promising tool for studying the distribution of polymers in biological systems.
Article
Microbiology
Alison J. Scott, Alexis A. Smith, Ron M. A. Heeren, Utpal Pal, Robert K. Ernst
Summary: Spatially aware de novo discovery methods play a crucial role in identifying therapeutic targets in complex interphylum interactions. This study evaluated the potential of matrix-assisted desorption/ionization mass spectrometry imaging (MALDI-MSI) as a spatial omics method to simultaneously profile an arthropod vector and a mammalian skin in a bite model. The results demonstrated the feasibility of using MSI to analyze lipids and observe lipid reorganization at the bite site in both the tick and mammalian skin.
Article
Chemistry, Analytical
Britt S. R. Claes, Kasper K. Krestensen, Gargey Yagnik, Andrej Grgic, Christel Kuik, Mark J. Lim, Kenneth J. Rothschild, Michiel Vandenbosch, Ron M. A. Heeren
Summary: A novel technique called MALDIIHC was published recently, which combines MALDI-MSI and IHC to achieve targeted imaging of biomolecules in tissue. This study explored the utility of targeted MALDIIHC and its complementarity with untargeted spatial proteomics using breast cancer tissue. The combination of multiplexed MALDI-IHC with image-guided proteomics showed great potential for disease investigation. Additionally, the effect of MALDI-2 in improving MALDI-IHC was investigated.
ANALYTICAL CHEMISTRY
(2023)
Article
Food Science & Technology
Mudita Vats, Berta Cillero-Pastor, Bryn Flinders, Eva Cuypers, Ron M. A. Heeren
Summary: This study utilized MALDI-MSI to determine the spatial distribution of flavor compounds in edible button mushrooms and optimized the sample preparation protocol and investigated the effect of heat on the distribution.
JOURNAL OF FOOD SCIENCE AND TECHNOLOGY-MYSORE
(2023)
Review
Chemistry, Analytical
Kasper K. Krestensen, Ron M. A. Heeren, Benjamin Balluff
Summary: Mass spectrometry imaging (MSI) has evolved from a niche technique to a widely used spatial biology tool. This review provides an overview of state-of-the-art MSI applications in both established and emerging biomedical fields, serving as a reference framework for new researchers in the field.
Article
Medical Laboratory Technology
Laura Van Hese, Steven De Vleeschouwer, Tom Theys, Emma Lariviere, Lien Solie, Raf Sciot, Tiffany Porta Siegel, Steffen Rex, Ron M. A. Heeren, Eva Cuypers
Summary: This study developed and validated a mass spectrometry-based technique for molecular characterization of high- and low-grade glioma tissue during surgery. The rapid evaporative ionization mass spectrometry (REIMS) technique could differentiate between different glioma subtypes with high accuracy, providing real-time information for intra-operative decision-making.
JOURNAL OF MASS SPECTROMETRY AND ADVANCES IN THE CLINICAL LAB
(2022)
