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Keywords = lensless camera

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17 pages, 2656 KB  
Article
Chip-Sized Lensless Holographic Microscope for Real-Time On-Chip Biological Sensing
by Sofía Moncada-Madrazo, Sergio Moreno, Oriol Caravaca, Joan Canals, Natalia Castro, Manel López, Javier Ramón-Azcón, Anna Vilà and Ángel Diéguez
Sensors 2025, 25(17), 5247; https://doi.org/10.3390/s25175247 - 23 Aug 2025
Viewed by 2072
Abstract
Microscopy is a fundamental tool in biological research. However, conventional microscopes require manual operation and depend on user and equipment availability, limiting their suitability for continuous observation. Moreover, their size and complexity make them impractical for in situ experimentation. In this work, we [...] Read more.
Microscopy is a fundamental tool in biological research. However, conventional microscopes require manual operation and depend on user and equipment availability, limiting their suitability for continuous observation. Moreover, their size and complexity make them impractical for in situ experimentation. In this work, we present a novel, compact, affordable, and portable microscope that enables continuous in situ monitoring by being placed directly on biological samples. This chip-sized lensless holographic microscope (CLHM) is specifically designed to overcome the limitations of traditional microscopy. The device consists solely of an ultra-compact, state-of-the-art micro-LED display and a CMOS sensor, all enclosed within a 3D-printed housing. This unique light source enables a size that is markedly smaller than any comparable technology, allowing a resolution of 2.19 μm within a 7 mm distance between the light source and the camera. This paper demonstrates the CLHM’s versatility by monitoring in vitro models and performing whole-organism morphological analyses of small specimens. These experiments underscore its potential as an on-platform sensing device for continuous, in situ biological monitoring across diverse models. Full article
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8 pages, 1322 KB  
Communication
Single Shot Lensless Interferenceless Phase Imaging of Biochemical Samples Using Synchrotron near Infrared Beam
by Molong Han, Daniel Smith, Soon Hock Ng, Tomas Katkus, Aravind Simon John Francis Rajeswary, Periyasamy Angamuthu Praveen, Keith R. Bambery, Mark J. Tobin, Jitraporn Vongsvivut, Saulius Juodkazis and Vijayakumar Anand
Biosensors 2022, 12(12), 1073; https://doi.org/10.3390/bios12121073 - 24 Nov 2022
Cited by 5 | Viewed by 2491
Abstract
Phase imaging of biochemical samples has been demonstrated for the first time at the Infrared Microspectroscopy (IRM) beamline of the Australian Synchrotron using the usually discarded near-IR (NIR) region of the synchrotron-IR beam. The synchrotron-IR beam at the Australian Synchrotron IRM beamline has [...] Read more.
Phase imaging of biochemical samples has been demonstrated for the first time at the Infrared Microspectroscopy (IRM) beamline of the Australian Synchrotron using the usually discarded near-IR (NIR) region of the synchrotron-IR beam. The synchrotron-IR beam at the Australian Synchrotron IRM beamline has a unique fork shaped intensity distribution as a result of the gold coated extraction mirror shape, which includes a central slit for rejection of the intense X-ray beam. The resulting beam configuration makes any imaging task challenging. For intensity imaging, the fork shaped beam is usually tightly focused to a point on the sample plane followed by a pixel-by-pixel scanning approach to record the image. In this study, a pinhole was aligned with one of the lobes of the fork shaped beam and the Airy diffraction pattern was used to illuminate biochemical samples. The diffracted light from the samples was captured using a NIR sensitive lensless camera. A rapid phase-retrieval algorithm was applied to the recorded intensity distributions to reconstruct the phase information. The preliminary results are promising to develop multimodal imaging capabilities at the IRM beamline of the Australian Synchrotron. Full article
(This article belongs to the Special Issue Photonic Sensors in Chemical and Biological Applications)
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12 pages, 4947 KB  
Article
Lensless Multispectral Camera Based on a Coded Aperture Array
by Jianwei Wang and Yan Zhao
Sensors 2021, 21(22), 7757; https://doi.org/10.3390/s21227757 - 22 Nov 2021
Cited by 7 | Viewed by 3999
Abstract
Multispectral imaging can be applied to water quality monitoring, medical diagnosis, and other applications, but the principle of multispectral imaging is different from the principle of hyper-spectral imaging. Multispectral imaging is generally achieved through filters, so multiple photos are required to obtain spectral [...] Read more.
Multispectral imaging can be applied to water quality monitoring, medical diagnosis, and other applications, but the principle of multispectral imaging is different from the principle of hyper-spectral imaging. Multispectral imaging is generally achieved through filters, so multiple photos are required to obtain spectral information. Using multiple detectors to take pictures at the same time increases the complexity and cost of the system. This paper proposes a simple multispectral camera based on lensless imaging, which does not require multiple lenses. The core of the system is the multispectral coding aperture. The coding aperture is divided into different regions and each region transmits the light of one wavelength, such that the spectral information of the target can be coded. By solving the inverse problem of sparse constraints, the multispectral information of the target is inverted. Herein, we analyzed the characteristics of this multispectral camera and developed a principle prototype to obtain experimental results. Full article
(This article belongs to the Section Remote Sensors)
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17 pages, 2035 KB  
Article
Compact Miniaturized Bioluminescence Sensor Based on Continuous Air-Segmented Flow for Real-Time Monitoring: Application to Bile Salt Hydrolase (BSH) Activity and ATP Detection in Biological Fluids
by Aldo Roda, Pierpaolo Greco, Patrizia Simoni, Valentina Marassi, Giada Moroni, Antimo Gioiello and Barbara Roda
Chemosensors 2021, 9(6), 122; https://doi.org/10.3390/chemosensors9060122 - 25 May 2021
Cited by 5 | Viewed by 4216
Abstract
A simple and versatile continuous air-segmented flow sensor using immobilized luciferase was designed as a general miniaturized platform based on sensitive biochemiluminescence detection. The device uses miniaturized microperistaltic pumps to deliver flows and compact sensitive light imaging detectors based on BI-CMOS (smartphone camera) [...] Read more.
A simple and versatile continuous air-segmented flow sensor using immobilized luciferase was designed as a general miniaturized platform based on sensitive biochemiluminescence detection. The device uses miniaturized microperistaltic pumps to deliver flows and compact sensitive light imaging detectors based on BI-CMOS (smartphone camera) or CCD technology. The low-cost components and power supply make it suitable as out-lab device at point of need to monitor kinetic-related processes or ex vivo dynamic events. A nylon6 flat spiral carrying immobilized luciferase was placed in front of the detector in lensless mode using a fiber optic tapered faceplate. ATP was measured in samples collected by microdialysis from rat brain with detecting levels as low as 0.4 fmoles. The same immobilized luciferase was also used for the evaluation of bile salt hydrolase (BSH) activity in intestinal microbiota. An aminoluciferin was conjugatated with chenodeoxycholic acid forming the amide derivative aLuc-CDCA. The hydrolysis of the aLuc-CDCA probe by BSH releases free uncaged aminoluciferin which is the active substrate for luciferase leading to light emission. This method can detect as low as 0.5 mM of aLuc-CDCA, so it can be used on real faecal human samples to study BSH activity and its modulation by diseases and drugs. Full article
(This article belongs to the Special Issue Microfluidic Biosensing Platform)
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11 pages, 5850 KB  
Tutorial
Lensless Three-Dimensional Quantitative Phase Imaging Using Phase Retrieval Algorithm
by Vijayakumar Anand, Tomas Katkus, Denver P. Linklater, Elena P. Ivanova and Saulius Juodkazis
J. Imaging 2020, 6(9), 99; https://doi.org/10.3390/jimaging6090099 - 20 Sep 2020
Cited by 30 | Viewed by 6617
Abstract
Quantitative phase imaging (QPI) techniques are widely used for the label-free examining of transparent biological samples. QPI techniques can be broadly classified into interference-based and interferenceless methods. The interferometric methods which record the complex amplitude are usually bulky with many optical components and [...] Read more.
Quantitative phase imaging (QPI) techniques are widely used for the label-free examining of transparent biological samples. QPI techniques can be broadly classified into interference-based and interferenceless methods. The interferometric methods which record the complex amplitude are usually bulky with many optical components and use coherent illumination. The interferenceless approaches which need only the intensity distribution and works using phase retrieval algorithms have gained attention as they require lesser resources, cost, space and can work with incoherent illumination. With rapid developments in computational optical techniques and deep learning, QPI has reached new levels of applications. In this tutorial, we discuss one of the basic optical configurations of a lensless QPI technique based on the phase-retrieval algorithm. Simulative studies on QPI of thin, thick, and greyscale phase objects with assistive pseudo-codes and computational codes in Octave is provided. Binary phase samples with positive and negative resist profiles were fabricated using lithography, and a single plane and two plane phase objects were constructed. Light diffracted from a point object is modulated by phase samples and the corresponding intensity patterns are recorded. The phase retrieval approach is applied for 2D and 3D phase reconstructions. Commented codes in Octave for image acquisition and automation using a web camera in an open source operating system are provided. Full article
(This article belongs to the Special Issue Current Highlights and Future Applications of Computational Imaging)
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14 pages, 4581 KB  
Article
Optical Lensless-Camera Communications Aided by Neural Network
by Suhua Zhong, Yuhong Zhu, Xuefen Chi, Hanyang Shi, Hongliang Sun and Shuang Wang
Appl. Sci. 2019, 9(16), 3238; https://doi.org/10.3390/app9163238 - 8 Aug 2019
Cited by 3 | Viewed by 2949
Abstract
Currently, the optical components of a camera embedded in the device constrain its overall thickness. Moreover, if the camera is strongly shaken, the lens and sensor may be misaligned, resulting in a defocusing effect. In this paper, we propose a novel lensless-camera communication [...] Read more.
Currently, the optical components of a camera embedded in the device constrain its overall thickness. Moreover, if the camera is strongly shaken, the lens and sensor may be misaligned, resulting in a defocusing effect. In this paper, we propose a novel lensless-camera communication model, which removes the lens of camera, therefore decreasing the overall thickness of the device without affecting communications. To decode the images captured by the lensless camera, a decoding algorithm aided by back propagation (BP) neural network was designed, which recognizes the blurred image patterns efficiently. To adapt to time-varying environments, an adaptive training sequence adjustment mechanism was designed. Simulation results show that the proposed image decoding algorithm presents a good bit-error-rate (BER) performance. The proposed system has robust movements and provides resilience to interference, benefiting from the neural network and the designed algorithm. Full article
(This article belongs to the Section Electrical, Electronics and Communications Engineering)
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13 pages, 3054 KB  
Article
Super Field-of-View Lensless Camera by Coded Image Sensors
by Tomoya Nakamura, Keiichiro Kagawa, Shiho Torashima and Masahiro Yamaguchi
Sensors 2019, 19(6), 1329; https://doi.org/10.3390/s19061329 - 16 Mar 2019
Cited by 19 | Viewed by 9884
Abstract
A lensless camera is an ultra-thin computational-imaging system. Existing lensless cameras are based on the axial arrangement of an image sensor and a coding mask, and therefore, the back side of the image sensor cannot be captured. In this paper, we propose a [...] Read more.
A lensless camera is an ultra-thin computational-imaging system. Existing lensless cameras are based on the axial arrangement of an image sensor and a coding mask, and therefore, the back side of the image sensor cannot be captured. In this paper, we propose a lensless camera with a novel design that can capture the front and back sides simultaneously. The proposed camera is composed of multiple coded image sensors, which are complementary-metal-oxide-semiconductor (CMOS) image sensors in which air holes are randomly made at some pixels by drilling processing. When the sensors are placed facing each other, the object-side sensor works as a coding mask and the other works as a sparsified image sensor. The captured image is a sparse coded image, which can be decoded computationally by using compressive sensing-based image reconstruction. We verified the feasibility of the proposed lensless camera by simulations and experiments. The proposed thin lensless camera realized super-field-of-view imaging without lenses or coding masks and therefore can be used for rich information sensing in confined spaces. This work also suggests a new direction in the design of CMOS image sensors in the era of computational imaging. Full article
(This article belongs to the Special Issue Advanced CMOS Image Sensors and Emerging Applications)
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19 pages, 17989 KB  
Article
Digital Holography as Computer Vision Position Sensor with an Extended Range of Working Distances
by Miguel Asmad Vergara, Maxime Jacquot, Guillaume J. Laurent and Patrick Sandoz
Sensors 2018, 18(7), 2005; https://doi.org/10.3390/s18072005 - 22 Jun 2018
Cited by 6 | Viewed by 4312
Abstract
Standard computer vision methods are usually based on powerful contact-less measurement approaches but applications, especially at the micro-scale, are restricted by finite depth-of-field and fixed working distance of imaging devices. Digital holography is a lensless, indirect imaging method recording the optical wave diffracted [...] Read more.
Standard computer vision methods are usually based on powerful contact-less measurement approaches but applications, especially at the micro-scale, are restricted by finite depth-of-field and fixed working distance of imaging devices. Digital holography is a lensless, indirect imaging method recording the optical wave diffracted by the object onto the image sensor. The object is reconstructed numerically by propagating the recorded wavefront backward. The object distance becomes a computation parameter that can be chosen arbitrarily and adjusted to match the object position. No refractive lens is used and usual depth-of-field and working distance limitations are replaced by less restrictive ones tied to the laser-source coherence-length and to the size and resolution of the camera sensor. This paper applies digital holography to artificial visual in-plane position sensing with an extra-large range-to-resolution ratio. The object is made of a pseudoperiodic pattern allowing a subpixel resolution as well as a supra field-of-observation displacement range. We demonstrate an in-plane resolution of 50 nm and 0.002deg. in X, Y and θ respectively, over a working distance range of more than 15 cm. The allowed workspace extends over 12×10×150mm3. Digital holography extends the field of application of computer vision by allowing an extra-large range of working distances inaccessible to refractive imaging systems. Full article
(This article belongs to the Section Physical Sensors)
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