A lens-free single-shot fluorescent imaging system using CMOS image sensors with dielectric multi-layer filter

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.

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Multi-Tap Charge Modulator Based Ultra-Fast Computational CMOS Image Sensors for Single-Shot and Repeatable Image Acquisition

Conference on Lasers and Electro-Optics ◽

10.1364/cleo_at.2020.jth1g.4 ◽

2020 ◽

Author(s):

Keiichiro Kagawa

Keyword(s):

Image Acquisition ◽

Image Sensors ◽

Single Shot ◽

Cmos Image Sensors

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Super Field-of-View Lensless Camera by Coded Image Sensors

10.20944/preprints201902.0265.v1 ◽

2019 ◽

Author(s):

Tomoya Nakamura ◽

Keiichiro Kagawa ◽

Shiho Torashima ◽

Masahiro Yamaguchi

Keyword(s):

Imaging System ◽

Complementary Metal Oxide Semiconductor ◽

Image Sensor ◽

Image Sensors ◽

Computational Imaging ◽

Field Of View ◽

Oxide Semiconductor ◽

Back Side ◽

Cmos Image Sensors ◽

Rich Information

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 realizes 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.

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1/f Noise Modelling and Characterization for CMOS Quanta Image Sensors

Sensors ◽

10.3390/s19245459 ◽

2019 ◽

Vol 19 (24) ◽

pp. 5459

Author(s):

Wei Deng ◽

Eric R. Fossum

Keyword(s):

Analog Circuits ◽

Image Sensor ◽

Image Sensors ◽

Correlated Double Sampling ◽

Cmos Image Sensors ◽

Source Follower ◽

Cmos Analog Circuits ◽

Different Origins ◽

Noise Models ◽

Fitting Model

This work fits the measured in-pixel source-follower noise in a CMOS Quanta Image Sensor (QIS) prototype chip using physics-based 1/f noise models, rather than the widely-used fitting model for analog designers. This paper discusses the different origins of 1/f noise in QIS devices and includes correlated double sampling (CDS). The modelling results based on the Hooge mobility fluctuation, which uses one adjustable parameter, match the experimental measurements, including the variation in noise from room temperature to –70 °C. This work provides useful information for the implementation of QIS in scientific applications and suggests that even lower read noise is attainable by further cooling and may be applicable to other CMOS analog circuits and CMOS image sensors.

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Effect of proton radiation on 8T CMOS image sensors for space applications

Radiation Effects and Defects in Solids ◽

10.1080/10420150.2021.1898391 ◽

2021 ◽

pp. 1-9

Author(s):

Jing Fu ◽

Jie Feng ◽

Yu-Dong Li ◽

Qi Guo ◽

Ying Wei ◽

...

Keyword(s):

Image Sensors ◽

Proton Radiation ◽

Space Applications ◽

Cmos Image Sensors

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Performance of a novel protease-activated fluorescent imaging system for intraoperative detection of residual breast cancer during breast conserving surgery

Breast Cancer Research and Treatment ◽

10.1007/s10549-021-06106-w ◽

2021 ◽

Vol 187 (1) ◽

pp. 145-153

Author(s):

Conor R. Lanahan ◽

Bridget N. Kelly ◽

Michele A. Gadd ◽

Michelle C. Specht ◽

Carson L. Brown ◽

...

Keyword(s):

Breast Cancer ◽

Real Time ◽

Imaging System ◽

Ex Vivo ◽

Menopausal Status ◽

Fluorescent Imaging ◽

Cancer Subtypes ◽

Surgical Workflow ◽

Tumor Types

Abstract Purpose Safe breast cancer lumpectomies require microscopically clear margins. Real-time margin assessment options are limited, and 20–40% of lumpectomies have positive margins requiring re-excision. The LUM Imaging System previously showed excellent sensitivity and specificity for tumor detection during lumpectomy surgery. We explored its impact on surgical workflow and performance across patient and tumor types. Methods We performed IRB-approved, prospective, non-randomized studies in breast cancer lumpectomy procedures. The LUM Imaging System uses LUM015, a protease-activated fluorescent imaging agent that identifies residual tumor in the surgical cavity walls. Fluorescent cavity images were collected in real-time and analyzed using system software. Results Cavity and specimen images were obtained in 55 patients injected with LUM015 at 0.5 or 1.0 mg/kg and in 5 patients who did not receive LUM015. All tumor types were distinguished from normal tissue, with mean tumor:normal (T:N) signal ratios of 3.81–5.69. T:N ratios were 4.45 in non-dense and 4.00 in dense breasts (p = 0.59) and 3.52 in premenopausal and 4.59 in postmenopausal women (p = 0.19). Histopathology and tumor receptor testing were not affected by LUM015. Falsely positive readings were more likely when tumor was present < 2 mm from the adjacent specimen margin. LUM015 signal was stable in vivo at least 6.5 h post injection, and ex vivo at least 4 h post excision. Conclusions Intraoperative use of the LUM Imaging System detected all breast cancer subtypes with robust performance independent of menopausal status and breast density. There was no significant impact on histopathology or receptor evaluation.

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