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Magnetic resonance imaging (MRI) offers superior soft tissue contrast and is widely used in biomedicine. However, conventional MRI is not quantitative, which presents a bottleneck in image analysis and digital healthcare. Typically,…

Quantum techniques can be used to enhance the signal-to-noise ratio in optical imaging. Leveraging the latest advances in single photon avalanche diode array cameras and multi-photon detection techniques, here we introduce a super-sensitive…

Lensless illumination single-pixel imaging with a multicore fiber (MCF) is a computational imaging technique that enables potential endoscopic observations of biological samples at cellular scale. In this work, we show that this technique…

Image and Video Processing · Electrical Eng. & Systems 2024-03-07 Olivier Leblanc , Mathias Hofer , Siddharth Sivankutty , Hervé Rigneault , Laurent Jacques

Quantum entanglement and squeezing have significantly improved phase estimation and imaging in interferometric settings beyond the classical limits. However, for a wide class of non-interferometric phase imaging/retrieval methods vastly…

Snapshot Multispectral Light-field Imaging (SMLI) is an emerging computational imaging technique that captures high-dimensional data (x, y, z, $\theta$, $\phi$, $\lambda$) in a single shot using a low-dimensional sensor. The accuracy of…

Signal Processing · Electrical Eng. & Systems 2025-09-03 Erqi Huang , John Restrepo , Xun Cao , Ivo Ihrke

Interferometry techniques are essential for extracting phase information from optical systems, enabling precise measurements of dispersion and highly sensitive detection of perturbations. While phase sensing offers enhanced sensitivity…

Deep learning has achieved tremendous success in computer vision, while medical image segmentation (MIS) remains a challenge, due to the scarcity of data annotations. Meta-learning techniques for few-shot segmentation (Meta-FSS) have been…

Computer Vision and Pattern Recognition · Computer Science 2023-03-08 Qianqian Shen , Yanan Li , Jiyong Jin , Bin Liu

Single-pixel imaging(SPI),especially when integrated with deep neural networks like deep image prior networks (DIP-Net) or data-driven networks (DD-Net), has gained considerable attention for its capability to generate high-quality…

Computational Physics · Physics 2025-12-01 Jing-yi Shi , Jia-qi Song , Peng-cheng Ji , Zi-qing Zhao , Yuan-jin Yu , Ming-fei Li , Ling-an Wu

In recent years, the introduction of deep learning into the field of single-pixel imaging has garnered significant attention. However, traditional networks often operate within the pixel space. To address this, we innovatively migrate…

Image and Video Processing · Electrical Eng. & Systems 2025-09-05 Chenyu Yuan

Magnetic resonance imaging (MRI) is a cornerstone of clinical neuroimaging, yet conventional MRIs provide qualitative information heavily dependent on scanner hardware and acquisition settings. While quantitative MRI (qMRI) offers intrinsic…

Hyperspectral pansharpening aims to synthesize a low-resolution hyperspectral image (LR-HSI) with a registered panchromatic image (PAN) to generate an enhanced HSI with high spectral and spatial resolution. Recently proposed HS…

Computer Vision and Pattern Recognition · Computer Science 2021-07-07 Wele Gedara Chaminda Bandara , Jeya Maria Jose Valanarasu , Vishal M. Patel

Real time, singleshot multispectral imaging systems are crucial for environment monitoring and biomedical imaging. Most singleshot multispectral imagers rely on complex computational backends, which precludes real time operations. In this…

Optics · Physics 2025-02-27 Romil Audhkhasi , Ningzhi Xie , Johannes E. Fröch , Arka Majumdar

Tissue biopsy evaluation in the clinic is in need of quantitative disease markers for diagnosis and, most importantly, prognosis. Among the new technologies, quantitative phase imaging (QPI) has demonstrated promise for histopathology…

Traditionally, spectroscopy is performed by examining the position of absorption lines. However, at frequencies near the transition frequency, additional information can be obtained from the phase shift. In this work we consider the…

Quantum Physics · Physics 2016-06-14 Hossein T. Dinani , Manish K. Gupta , Jonathan P. Dowling , Dominic W. Berry

We present a simple and effective method to eliminate system aberrations and speckle noise in quantitative phase imaging. Using spiral integration, complete information about system aberration is calculated from three laterally shifted…

Biological Physics · Physics 2018-02-14 Inhyeok Choi , Kyeoreh Lee , YongKeun Park

Quantum State Tomography (QST) has been the traditional method for characterization of an unknown state. Recently, many direct measurement methods have been implemented to reconstruct the state in a resource efficient way. In this letter,…

Quantum Physics · Physics 2020-09-23 Surya Narayan Sahoo , Sanchari Chakraborti , Arun K. Pati , Urbasi Sinha

Coded wavefront sensing (Coded-WFS) is a snapshot quantitative phase imaging (QPI) technique that has been shown to successfully leverage the memory effect to retrieve the phase of biological specimens. In this paper, we perform QPI on…

Snapshot compressive imaging (SCI) captures multispectral images (MSIs) using a single coded two-dimensional (2-D) measurement, but reconstructing high-fidelity MSIs from these compressed inputs remains a fundamentally ill-posed challenge.…

Image and Video Processing · Electrical Eng. & Systems 2025-12-02 Shaoguang Huang , Yunzhen Wang , Haijin Zeng , Hongyu Chen , Hongyan Zhang

Experimental quantum simulators have become large and complex enough that discovering new physics from the huge amount of measurement data can be quite challenging, especially when little theoretical understanding of the simulated model is…

Quantum Physics · Physics 2020-12-08 Alexander Lidiak , Zhexuan Gong

Quantitative magnetic resonance imaging (qMRI) is concerned with estimating (in physical units) values of magnetic and tissue parameters e.g., relaxation times $T_1$, $T_2$, or proton density $\rho$. Recently in [Ma et al., Nature, 2013],…

Optimization and Control · Mathematics 2019-03-29 Guozhi Dong , Michael Hintermüller , Kostas Papafitsoros
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