WO2022087657A1 - Outil intelligent non invasif pour la surveillance continue de virus et la détection rapide de virus connus et inconnus - Google Patents

Outil intelligent non invasif pour la surveillance continue de virus et la détection rapide de virus connus et inconnus Download PDF

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Publication number
WO2022087657A1
WO2022087657A1 PCT/AU2021/051240 AU2021051240W WO2022087657A1 WO 2022087657 A1 WO2022087657 A1 WO 2022087657A1 AU 2021051240 W AU2021051240 W AU 2021051240W WO 2022087657 A1 WO2022087657 A1 WO 2022087657A1
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nanoparticles
film
thin metal
sample
image sensor
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PCT/AU2021/051240
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English (en)
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Ibrahim Elgendi
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Ibrahim Elgendi
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Priority claimed from AU2020903930A external-priority patent/AU2020903930A0/en
Application filed by Ibrahim Elgendi filed Critical Ibrahim Elgendi
Publication of WO2022087657A1 publication Critical patent/WO2022087657A1/fr

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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/62—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light
    • G01N21/63—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light optically excited
    • G01N21/64—Fluorescence; Phosphorescence
    • G01N21/6486—Measuring fluorescence of biological material, e.g. DNA, RNA, cells
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/62—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light
    • G01N21/63—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light optically excited
    • G01N21/64—Fluorescence; Phosphorescence
    • G01N21/645—Specially adapted constructive features of fluorimeters
    • G01N21/6456—Spatial resolved fluorescence measurements; Imaging
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/59—Transmissivity
    • G01N21/5907—Densitometers
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/62—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light
    • G01N21/63—Systems in which the material investigated is excited whereby it emits light or causes a change in wavelength of the incident light optically excited
    • G01N21/64—Fluorescence; Phosphorescence
    • G01N21/645—Specially adapted constructive features of fluorimeters
    • G01N21/648—Specially adapted constructive features of fluorimeters using evanescent coupling or surface plasmon coupling for the excitation of fluorescence
    • G—PHYSICS
    • G02—OPTICS
    • G02B—OPTICAL ELEMENTS, SYSTEMS OR APPARATUS
    • G02B21/00—Microscopes
    • G02B21/16—Microscopes adapted for ultraviolet illumination ; Fluorescence microscopes
    • G—PHYSICS
    • G02—OPTICS
    • G02B—OPTICAL ELEMENTS, SYSTEMS OR APPARATUS
    • G02B5/00—Optical elements other than lenses
    • G02B5/008—Surface plasmon devices
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N20/00—Machine learning
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B82—NANOTECHNOLOGY
    • B82Y—SPECIFIC USES OR APPLICATIONS OF NANOSTRUCTURES; MEASUREMENT OR ANALYSIS OF NANOSTRUCTURES; MANUFACTURE OR TREATMENT OF NANOSTRUCTURES
    • B82Y15/00—Nanotechnology for interacting, sensing or actuating, e.g. quantum dots as markers in protein assays or molecular motors
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B82—NANOTECHNOLOGY
    • B82Y—SPECIFIC USES OR APPLICATIONS OF NANOSTRUCTURES; MEASUREMENT OR ANALYSIS OF NANOSTRUCTURES; MANUFACTURE OR TREATMENT OF NANOSTRUCTURES
    • B82Y20/00—Nanooptics, e.g. quantum optics or photonic crystals
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N21/00—Investigating or analysing materials by the use of optical means, i.e. using sub-millimetre waves, infrared, visible or ultraviolet light
    • G01N21/17—Systems in which incident light is modified in accordance with the properties of the material investigated
    • G01N21/59—Transmissivity
    • G01N21/5907—Densitometers
    • G01N2021/5957—Densitometers using an image detector type detector, e.g. CCD
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N3/00—Computing arrangements based on biological models
    • G06N3/02—Neural networks
    • G06N3/08—Learning methods
    • G06N3/088—Non-supervised learning, e.g. competitive learning

Definitions

  • a lateral flow immunoassay which is a common point-of-care (POC) diagnostic approach that detects antibodies against specific viruses (e.g., SARS-CoV-2) in patient samples
  • POC point-of-care
  • Biosensors based on liposome technology have been used for several years in the diagnosis of a single virus once test at a time. They have severe limitations. For example, they are more expensive, cannot detect unknown virus if virus modified its gene (Mutated Virus), and cannot detect virus in real-time and automatic way.
  • a lens-free imaging system equipped with thin metal-film and Artificial Intelligent (Al) for detecting nanoparticles or virus in a sample deposited on thin metal-film includes a thin metal-film for holding a sample and create shadow image, an image sensor for imaging and capture the sample shadow image, and controller to detect shadow image(s) using Al.
  • This imaging system designed to collect virus’ data such as shape, size, ribonucleic Acid (RNA) or DNA structure for each virus.
  • a method for detecting nanoparticles or virus of interest in a sample deposited on thin metal-film, which deposited directly on the image sensor includes (i) generating enhanced detection sensitivity of shadow image using thin metal-film to create Surface-Enhanced Fluorescence (SEF).
  • SEF Surface-Enhanced Fluorescence
  • SPP Surface Plasmon Polaritons
  • FIG. 1 illustrates one lens-free imaging system that includes thin metal-film for creating shadow images excited by Ultraviolet (UV) light source and capture by using image sensor and detecting nanoparticles in a sample deposited on thin metal-film by using Al in the controller, according to one embodiment.
  • UV Ultraviolet
  • FIG. 2 illustrate the thin metal-film including four layers starting from Quartz with 10 nanometres (nm), Titanium (Ti) with 3 nm, gold (Au) with 10 nm, and silicon oxide (SiO2) with 15 nm, according to an embodiment.
  • FIG. 3 illustrates controller with its components to detect and control shadow images that are created by lens-free image system with thin metal-film, according to an embodiment.
  • FIG. 4 illustrates one lens-free imaging system with thin metal-film for detecting nanoparticles in a sample deposited on the thin metal-film, which includes thin metal-film, image sensor, and controller of FIG. 1, FIG. 2, and FIG. 3, according to an embodiment.
  • FIG. 5 illustrates nanoparticles using one lens-free imaging method for sample deposited on thin metalfilm for detecting Al, according to an embodiment.
  • FIG. 6 illustrates SEF and transmission effects of thin metal-film for air as a media and a sample deposited on the thin metal-film, according to an embodiment.
  • FIG. 7 illustrates SEF and transmission effects for light incident on SiO2 layer of the thin metal-film.
  • FIG. 8 illustrates SEF, SPP, transmission, absorption, and reflection effects for a plane wave of Ultraviolet (UV) light incident on Ti and Au layers of thin metal-film respectively, according to an embodiment.
  • UV Ultraviolet
  • FIG. 9 illustrates one lens-free imaging system with sample deposited on thin metal-film and Al embedded in controller for detecting nanoparticles, which includes the imaging system of FIG. 6, FIG. 7, and FIG. 8, according to an embodiment.
  • FIG. 10 illustrates one lens-free method equipped with thin metal-film and Al for detecting nanoparticles in a sample deposited on the thin metal-film, to generate a shadow image using the image sensor and thin metal-film, according to an embodiment.
  • FIG. 11 illustrates one lens-free imaging equipped with thin metal-film and Al method for detecting nanoparticles based on their geometrical features, RNA, and/or DNA in a sample deposited on the thin metal-film in a shadow image, according to an embodiment.
  • FIG. 12 illustrates one lens-free fluorescence imaging of nanoparticles such as viruses in a sample deposited on the thin metal-film used to image the sample that deposited directly on image sensor, according to an embodiment.
  • FIG. 13 illustrates one lens-free imaging system equipped with thin metal-film and Al for detecting unknown nanoparticles such as viruses in a sample deposited on the thin metal-film, which includes the imaging system of FIG. 12, according to an embodiment.
  • FIG. 14 illustrates one lens-free imaging equipped with thin metal-film and Al for performing lens-free fluorescence imaging, using an image sensor, thin metal-film and Al, of unknown nanoparticles such as viruses in a sample deposited on the thin metal-film, according to an embodiment.
  • FIG. 15 illustrates one lens-free imaging equipped with thin metal-film and Al method for extracting and detecting unknown nanoparticles based on their geometrical, RNA, and/or DNA features in a sample deposited on the thin metal-film in a fluorescence image, according to an embodiment.
  • FIG. 1 illustrates one exemplary lens-free imaging device equipped with thin metal-film, image sensor, and Al embedded in controller system 100 for detecting nanoparticles 104 in a sample 103 deposited on thin metal-film 105.
  • the imaging part of imaging device 100 includes thin metal-film 105 disposed directly on the image sensor 106, according to an embodiment.
  • Thin metal-film 105 that is in close proximity to photosensitive pixel elements of image sensor 106.
  • Lens- free imaging equipped with thin metal-film and Al system 100 includes an UV light source 102 with incident angle 101 that excites thin metal-film 105 to create SEF. The resulted transmitted light from thin metal-film 105 excited the nanoparticles 104 in sample 103 to generate SPP.
  • lens-free imaging equipped with thin metal-film and Al system 100 does not include an imaging objective between thin metal-film 105 and photo sensitive pixel array of image sensor 106 and instead performs lens- free imaging of sample 103 when in thin metal-film 105.
  • lens-free imaging equipped with thin metal-film and Al system refers to imaging without use of an imaging objective, i.e., the image is formed on image sensor 106 without use of focusing (refractive or diffractive) elements.
  • Lens-free imaging 100 instead utilizes the close proximity between thin metal-film 105 and photosensitive pixel array of image sensor 106 to generate one or more images of sample 103 in thin metal-film 105 using image sensor 106.
  • FIG. 1 shows controller 107 that displays, processes, and detects images of nanoparticles 104 of sample 103 that is disposed on thin metal-film 105 that is disposed directly on image sensor 106.
  • controller 107 includes Al modules to detect nanoparticles 104 in sample 103 using DL. The components of Al are not shown in FIG. 1.
  • Sample 103 is, for example, a blood or water sample, a human blood sample, animal blood sample, plant sample a nasal Swab and a urine samples, or another biological sample
  • nanoparticles 104 of interest in sample 103 may include one or more of blood cells, tissue cells, cancer, bacteria, pathogens, or viruses.
  • image sensor 106 is a complementary metal oxide semiconductor (CMOS) image sensor.
  • CMOS complementary metal oxide semiconductor
  • image sensor 106 is a backside illuminated CMOS image sensor with improved light sensitivity, as compared to a frontside illuminated CMOS image sensor.
  • UV light source 102 is, for example, a laser diode that produce UV light. UV Light source 102 has angle 101 to direct UV light towards thin metal-film 105.
  • Lens-free imaging with thin metal-film and Al embedded in controller system 100 provides simple and relatively inexpensive detection of nanoparticles such as viruses. Since lens-free imaging with thin metalfilm and Al system 100 performs lens-free imaging of sample 103, the manufacture of lens-free imaging with thin metal-film and Al system 100 does not require the manufacture of an imaging objective nor alignment of an imaging objective with respect to image sensor 106 and/or UV light Source 102; this simplifies manufacture of lens -free imaging with thin metal-film and Al system 100 and reduces the amount of materials included in lens-free imaging with thin metal-film and Al system 100, improves compactness, and makes detection of nanoparticles is smart and automatic process without any manual intervention from doctors or nurses or hospitals.
  • lens-free imaging with thin metal-film and Al system 100 may provide a more compact and cost-effective solution than competing traditional lens-free or lens-based imaging Systems, lens-free imaging with thin metal-film and Al system 100 can be used as a home-test device that can give results in a very short time with high accuracy and in an automatic way without any manual intervention from doctors, nurses, hospitals, and clinics by using Al software.
  • lens-free imaging with thin metal-film and Al system 100 is operated in an automatic mode, wherein sample 103 is first disposed on thin metal-film 105 and then captured by image sensor 106 and detected by Al. After completing imaging of sample 103, sample 103 may be cleaned out of thin metal-film 105 to prepare thin metal-film 105 for imaging of another sample 103, such that thin metal-film 105 is reusable for imaging of multiple different samples 103 or replacing the old thin metalfilm with a new one to avoid stacked virus or nanoparticles on thin metal-film surface.
  • FIGs. 2A and 2B illustrate further exemplary details of thin metal-film 105 (FIG. 1).
  • FIG. 2A shows thin metal-film 105 in cross sectional view, where the cross section is taken in the plane of thin metal-film 105.
  • FIG. 2B shows thin metal-film 105 in cross sectional view, where the cross section is taken in a plane orthogonal to the plane of thin metal-film 105.
  • the bottom of a SiO2 layer 204 disposed on pixel array of image sensor 106 As illustrated in FIGs. 2A and 2B, the bottom of a SiO2 layer 204 disposed on pixel array of image sensor 106.
  • the distance between SiO2 layer 204 and pixel array of image sensor 106 is significantly smaller and based on the size of nanoparticles 104 of sample 103.
  • Layers 201, 202, 203, and 204 form thin metal-film 105. in the embodiment of FIGs 2 A and 2B.
  • Layer 201 is for example quartz and cover layer 202 is at least partially transmissive to light.
  • at least a large a portion of light generated by UV light source 102 pass through Ti layer 202 and Au layer 203.
  • Au layer 203 is plasmonic designed to at least a large part of transmitted light passes through SiO2 layer 204.
  • SiO2 layer 204 is for example cover nanoparticles 104 in sample 103 is at least partially transmissive to
  • FIG. 3 further exemplary details of controller 107 (FIG. 1) for controlling, classifying, and detection of nanoparticles 104 in a sample 103 deposited on the thin metal-film 105 and image sensor 106 are used to image the sample, controller 107 is an embodiment of lens-free imaging with thin metal-film and Al system 100 (FIG. 1). Controller 107 controls the functionality of image sensor 105 and provides power supply (5.0 DC V) to UV light source 102. Controller 107 receives and controls the shadow images created by image sensor 106 for nanoparticles 104 of sample 103 by using Industry Processor Interface and Camera Serial Interface (MIPI CSI) 305. Controller 107 includes many components to control the images that are created by thin metal-film 105 and captured by image sensor 106.
  • MIPI CSI Industry Processor Interface and Camera Serial Interface
  • controller 107 includes 2 USB ports 301 that the port is capable of being used as a true On-The-Go (OTG) port.
  • the two USB 301 are used to connect the controller 107 with keyboard and mouse.
  • controller 107 includes image sensor room 302.
  • Image sensor room 302 consists of upper part and lower part, the upper part of the image sensor room 302 is the tray that host thin metal-film 105 and nanoparticles 104 of sample 103 and facing UV light source 102.
  • the lower part of image sensor room 302 hosts the image sensor 106 that connects to MIPI CSI 305 on the controller.
  • Another controller 107 component is High-Definition Multimedia Interface (HDMI) 306.
  • HDMI 306 is used to connect the controller 107 with display unit such as digital TV or computer display.
  • Micro USB 307 on the controller is used to supply power (5 DC V/2.5A DC) into the controller 107.
  • Wireless module 309 on the controller 107 is used to provide the controller with wireless connection. Wireless module 309 is used to connect the controller 107 to the Internet or other wireless networks for data exchange.
  • General-Purpose Input/Output (GPIO) 310 on the controller 107 is used to supply power (5.0V DC) to UV light source 102.
  • the processor 312 of controller 107 is used for control and process data, image, and any running processes by controller 107.
  • 1GB LPDDR2 SDRAM 313 of controller 107 is used as permeant data storage.
  • Fixture 303 of controller 107 is used to fix the controller 107 and its components to the enclosure.
  • SD card 308 The most important component of controller 107 is SD card 308.
  • SD card 308 is used for loading operating system and data storage. Also, it used for loading Al software.
  • SUBSTITUTE SHEET (RULE 26) 308 has technological advantages in that it effectively consists of multiple modules, which each module design describes each type of nanoparticles 104.
  • a module will describe the COVID-19 features of nanoparticles 104 such as shape, size, RNA and/or DNA sequences while the other to describe the features of SARS-1 of nanoparticles 104 but the most important module will be the module to describe the features of unknown nanoparticles 104 or the mutations of nanoparticles 104.
  • This module will describe the shape, size, and gene modification of nanoparticles 104 to detect it even if it modified its gene. As a result, the present invention will detect and predict nanoparticles 104 more rapidly and consistently and in automatic manner.
  • FIG. 4 illustrates one exemplary lens-free imaging equipped with thin metal-film, image sensor, and Al system 400 for detection of nanoparticles in a sample deposited on the thin metal-film that deposited directly on image sensor that used to capture the sample image.
  • Imaging system 400 is an embodiment of lens-free imaging equipped with thin metal-film and Al system 100 (FIG. 1).
  • the imaging system 400 includes thin metal-film 105 (FIGs. 1, 2A, and 2B), image sensor 106, UV light source 102 (FIG. 1), and a controller 107 (FIG. 3). Controller 107 controls the functionality of thin metal-film 105, image sensor 106 and operation power of UV light source 102.
  • Light source 102 illuminates the thin metal-film 105, which, as shown in FIGs. 2 A and 2B, is in direct contact with image sensor 106 to capture an image of nanoparticles 104 through light receiving by pixel array of image sensor 106.
  • Lens-free imaging with thin metal-film and Al system 400 is shown with controller 107 that analyses images created by thin metal-film 105 and captured by image sensor 106.
  • the controller 107 includes a processor 312 (FIG. 3) and memory 313 (FIG. 3).
  • Memory 313 includes 1GB LPDDR2 SDRAM.
  • controller 107 includes other components as mentioned in previous sections such as USB port 301, wireless module 309, GPIO 310, 4 pole stereo output 304, MIPI CSI camera port 305, HDMI 306, Micro USB 307, and SD card 308 that hosting Al modules.
  • the system 400 includes an enclosure 490.
  • the imaging system 400 includes wireless interface 309 for communicating and connecting with the internet and another network. Also, the system 400 includes 4 pole stereo output 304 to deliver the output results that created automatically by using Al in SD card 308.
  • the system 400 can be home-test device equipped with thin metal-film and Al to deliver the test results automatically through 4 pole stereo output 304 by connecting headphone to hear the voice message.
  • the system 400 uses HDMI 306 USB port 301 to configure image sensor 106 and Al in SD card 308.
  • Al in SD card 308 receives commands from the operator or the external system and communicates these instructions to control the controller 107.
  • Al in SD card 308 also serves to communicate data, such as images data extracted from thin metal-film 105 and image sensor 106, from analysis module 310 to an operator or an external system.
  • MIPI camera port 306 sends images, created by thin metal-film 105 and captured by image sensor 106, directly to Al in SD card 308 for analysis and running Al software for detection.
  • the system 400 includes input power 307 that supplies power to image sensor 106, controller 107.
  • the controller 107 includes GPIO 310 that supplies power to UV light source 102.
  • FIG. 5 illustrates one exemplary method 500 for detecting nanoparticles in a sample deposited on thin metal-film that deposited inside tray and disposed directly on pixel arrays of image sensor 106.
  • Method 500 utilizes lens-free imaging of a sample disposed in thin metal-film deposited inside tray and put over pixel array of image sensor 106.
  • Method 500 is performed, for example, by imaging system 100 or 400 of FIGs. 1 and 4, respectively.
  • the sample is deposited on the thin metal-film that deposited in the tray.
  • sample 103 (FIG. 1) is deposited on the thin metal-film 105 (FIGs. 1, 2 A, 2B, and 4) that put inside the tray and the tray with the thin metal-film and sample deposited on the pixel array of image sensor 106 inside image sensor room 302.
  • step 520 the image sensor with thin metal-film, onto which the sample is deposited in step 510, performs lens-free imaging of the sample to produce an image thereof.
  • thin metal-film 105 generates the required transmitted light through the sample 103 using SEF and image sensor 106 captures an image of sample 103 deposited on thin metal-film 105 in step 510.
  • controller 107 FIG. 3
  • the image sensor 106 is configured and controlled to capture images at regular intervals and give the results in automatically way through 4 pole stereo port 304 (FIGs. 3, and 4) when powered on.
  • step 520 is repeated one or more times to generate a plurality of images of the sample.
  • Step 520 includes steps 522 and 523.
  • the sample is illuminated.
  • UV light source 102 (FIGs. 1 and 4) illuminates thin metal-film 105 to excite sample 103 to create SPP.
  • the image sensor uses a photosensitive pixel array to detect light from thin metal-film transmitted through the sample 103.
  • pixel array of image sensor 106 (FIGs. 1, and 4) to detect light incident on thin metal-film 105. Since thin metal-film 105 is in direct contact with image sensor 106, a sample deposited on thin metal-film 105 is in close proximity to pixel array of image sensor 106. This facilitates lens-free imaging of the sample deposited on thin metal-film 105.
  • step 530 nanoparticles of interest are detected in the image, or images, generated in step 520.
  • processor 312 (FIGs.3, and 4) of controller 107 (FIGs.l, 3 and 4) executes instructions of Al in SD card 308 (FIGs.3, and 4) to detect nanoparticles of interest in an image received from image sensor 106.
  • Step 530 may further include processing to detect nanoparticles of interest to produce other results, such as the number of concentration of one or more nanoparticles of interest or properties of one or more nanoparticles of interest.
  • step 540 images feature of nanoparticles of interest are extracted by using Al in SD card 308 (FIGs.3, and 4). Images features of nanoparticles of interest extracted in step 540 and images generated in step 520 and/or results extracted therefrom in step 530 are outputted.
  • image sensor 106 outputs images generated by image sensor 106 to send to MIPI CSI camera port 305 (FIGs.3, and 4) to be controlled by controller 107.
  • Al used DL modules resided in SD card 308 to train and create datasets of images of nanoparticles of interest that are captured by image sensor 106.
  • Al and DL modules extracted the nanoparticles of interest features from created datasets. DL created models for nanoparticles of interest using its extracted features to detect the nanoparticles of interest.
  • FIG. 6 illustrates one exemplary thin metal-film 600 for performing light transmission through a sample, such as sample 103 of FIG. 1, to generate a shadow image of the sample.
  • Thin metal-film 600 is an embodiment of lens-free imaging equipped with thin metal-film and Al systemlOO (FIGs.l, 2A, and 2B) tailored for shadow imaging a sample.
  • Thin metal-film 600 includes four layers 201, 202, 203, and 204 (FIGs.l, 2A, and 2B) disposed thereupon.
  • FIG. 6 depicts thin metal-film 600 in the same cross-sectional view as used in FIG. 2B.
  • Thin metal-film 600 includes layer 201 with thickness 10 nm is for example quartz and cover Ti layer 202 with thickness 3 nm is at least partially transmissive to light. Hence, at least a large a portion of light generated by UV light source 102 pass through Ti layer 202.
  • Ti Layer 202 with thickness 3 nm is for example cover Au layer 203 is at least partially transmissive to light. Hence, at least a large a portion of light generated by UV light source 102 pass through Au layer 203.
  • Au layer 203 is for example cover layer 204 is at least partially transmissive to light. Hence, at least a large a portion of light generated by UV light source 102 is transmitted through layer 204.
  • Layer 204 is for example SiO2 and cover nanoparticles 104 in sample 103 is at least partially transmissive to light. Hence, at least a large a portion of light transmitted by layer 204 passes through nanoparticles 104 in sample 103 to illuminate nanoparticles 104.
  • Thin metalfilm 600 designed for air medium 610. The transmitted light through different layers based on SEF and SPP phenomena.
  • Plot 620 shows the intensity profile of transmission efficiency T(x) plotted in arbitrary intensity units of transmission efficiency 605 as a function of wavelength 604 in units of nanometres.
  • This example is representative of, for example, angle 101 of 51 degree with a wavelength of 450 to 630 nm incident on Quartz layer.
  • FIG. 7 illustrates one exemplary thin metal-film 700 for performing light transmission through a sample, such as sample 615, to generate a shadow image of the sample. Also, FIG. 7 shows the effect of transmission efficiency for a plane wave of UV light incident on SiO2 layer of thin metal-film 700.
  • the thin metal-film 700 includes Quartz layer 201, Ti layer 202, Au layer 203, SiO2 layer 204, and pixel array of image sensor 106, as illustrated in FIG. 6, provided by blood sample 615 deposited on SiO2 layer 204.
  • Image sensor 106 is configured to capture a shadow image of a sample deposed on thin metal-film 105.
  • the shadow image is formed by exposing thin metal-film 105 to UV light source 102 (FIG. 1).
  • illumination from UV light source 102 is at least partially blocked by sample 615 to form corresponding shadows on pixel array of image sensor 106.
  • nanoparticles in sample 615 are identifiable as shadows, in a shadow image captured by image sensor 106 using its pixel array.
  • metal-film 105 is designed to receive illumination of UV light source 102 having invisible spectrum wavelength, for example in the range from 400 to 630 nanometres.
  • Al in SD card 308 (FIGs.3, and 4) is configured to detect geometrical properties of nanoparticles in sample 615, such as size and/or shape, of nanoparticles deposed on SiO2 layer through determination of the size and shape of shadows for images are captured by image sensor 105 associated with the nanoparticles.
  • the wavelength of UV light source 102, the incident angle 101, the distance from laser diode of UV light source to Quartz layer 101, and the distance from SiO2 layer 204 to nanoparticles of interest in thin metal-film 105 are matched to the size of the nanoparticles of interest to minimize or reduce diffraction effects in the image captured by image sensor 106 and enhance SEF and SPP.
  • Diffraction occurs when illumination of UV light source 102 interacts with nanoparticles 104 deposited on thin metal-film 105.
  • the degree to which a shadow formed by a nanoparticle between SiO2 layer 204 and pixel array of image sensor 106 exhibits diffraction effects is determined by the Fresnel number and SEF characteristics and SPP analysis.
  • Plots 701 shows light transmission efficiency profile T(x) for SiO2 layer with different thickness.
  • Plot 701 shows the intensity profile of transmission efficiency T(x) plotted in arbitrary intensity units of transmission efficiency 605 as a function of wavelength 604 in units of nm.
  • SUBSTITUTE SHEET (RULE 26) Plot 701 shows the intensity of light transmitted T(x) through SiO2 layer 204, labelled 702, 703, 704, 705, 706, 707, 708, 709, 710, and 711 for thickness from 45 nm to 0 nm respectively.
  • This example is representative of, for example, angle 101 of (-51°) with a wavelength of 450 to 630 nm incident on Quartz layer.
  • FIG. 8 illustrates the effect of SEF of Ti layer 202 and Au layer 203 that are excited by UV light source 102 with illumination angle 101 to generate SPP.
  • SEF phenomenon on a planar thin metal-film 105 is strongly dependent on several variables such as the Ti, Au, and SiO2 thicknesses, the illumination angle (0) 101, the excitation polarization and wavelength.
  • Fluorescence Intensity at the Optimal Angle at Base Line Quartz Layer 203 where AMF is obtained by dividing the average fluorescence intensity of target nanoparticles 104 at the optimal illumination angle 101 (yielding maximum fluorescence) by their base line intensity in the angular intensity spectrum of a given plasmonic film design.
  • EF is obtained by dividing the average fluorescence intensity of nanoparticles 104 on gold films at the optimal illumination angle 101 with the average fluorescence intensity that can be obtained on a bare glass using an optimal illumination angle 101 (-51°).
  • Plots 800 shows the intensity of light transmitted, reflected, and absorbed T(x) for Ti layer 202.
  • Plot 800 shows the intensity of light transmitted, reflected, and absorbed T(x) plotted in arbitrary intensity units as a function of wavelength 604 in units of nm.
  • Plot 800 shows the intensity of light transmitted, reflected, and absorbed T(x) through Ti layer 202, labelled 803, 801, and 802 respectively.
  • This example is representative of, for example, angle 101 of (-51°) with a wavelength of 450 to 630 nm incident on Quartz layer 201.
  • Plots 820 shows the intensity of light transmitted, reflected, and absorbed T(x) for Au layer 203.
  • Plot 820 shows the intensity of light transmitted, reflected, and absorbed T(x) plotted in arbitrary intensity
  • SUBSTITUTE SHEET (RULE 26) units as a function of wavelength 604 in units of nm.
  • Plot 820 shows the intensity of light transmitted, reflected, and absorbed T(x) through Au layer 203, labelled 822, 823, and 821 respectively.
  • This example is representative of, for example, illumination angle 101 (-51°) with a UV light source wavelength of 447 nm incident on Quartz layer 201 to give maximum transmission intensity T(x) as shown in plot 820.
  • FIG. 9 illustrates one exemplary lens-free imaging equipped with thin metal-film and Al system 900 for detecting nanoparticles, which utilizes thin metal-film to create SEF to create lens-free shadow images of a sample deposited on the SiO2 layer and deposited directly on pixel array of image sensor that used to capture the shadow image(s).
  • System 900 is an embodiment of system 100 (FIG. 1) similar to imaging system 400 (FIG. 4).
  • imaging system 900 that includes thin metalfilm and image sensor in design 700 (FIG. 7) instead of thin metal-film 105 and image sensor 106 (FIGs.l, 2, and 4), and includes Al instructions 920 instead of SD card 308 (FIG. 4) only.
  • Al instructions 920 includes automatic nanoparticles images analysis 930, automatic nanoparticles geometric criteria analysis 940, and automatic nanoparticles RNA and DNA analysis 950.
  • Al Instructions 920 include automatic nanoparticles shadow image analysis instructions 930 that, when executed by processor 312, identify nanoparticles of interest in shadow images generated by thin metal-film and captured by image sensor as system 700 (FIG. 7).
  • Automatic nanoparticles geometric criteria analysis 940, and automatic nanoparticles RNA and DNA analysis 950 further include Al algorithms to train, model, extract, and create datasets of nanoparticles geometric criteria, RNA, and DNA features.
  • Al instructions in automatic nanoparticles geometric criteria analysis 940 retrieves the geometrical criteria such as size and shape to identify nanoparticles of interest based upon geometrical properties of shadows in shadow images generated by thin metal-film and captured by image sensor as system 700.
  • Al instructions automatic nanoparticles RNA and DNA analysis 950 creates RNA and DNA model of nanoparticles of interest to retrieve the gene structure to identify nanoparticles of interest based upon gene properties of shadows in shadow images generated by thin metal-film and captured by image sensor system 700.
  • Al instructions in automatic nanoparticles RNA and DNA analysis 950 is used to detect unknown nanoparticles. For example, it is used to detect unknown virus based on RNA and/or DNA sequences.
  • FIG. 10 illustrates one exemplary method 1000 for generating a shadow image of a sample, deposited on thin metal-film, through lens-free imaging of the sample using thin metal-film to generate shadow images and the image sensor to capture the shadow images.
  • Method 1000 is an embodiment of step 520 of method 500 (FIG. 5) and may be performed by imaging system 900 (FIG. 9).
  • the thin metal-film generates SEF to enhance detection sensitivity of a shadow image of a sample located on the S1O2 layer 204 of the thin metal-film, and an image sensor captures a shadow image to perform lens-free imaging.
  • Step 1010 includes concurrent steps 1020 and 1030.
  • the sample is excited to create SPP.
  • UV light source 102 (FIGs.l and 9) provides illumination to illuminate the thin metal-film to create SEF and excite a sample, such as sample 103 (FIG. 1), deposit on thin metal-film 105 (FIGs. 1 and 9) that is located on imaging sensor system 700 (FIGs.7 and 9).
  • step 1030 light transmitted by the thin metal-film and through sample is captured using a photosensitive pixel array of the image sensor.
  • pixel array in image sensor (FIG. 7) captures transmitted light of thin metal-film and that is transmitted by the sample.
  • step 1030 includes a step 1040 of performing the detection using SEF that maximizes or increases transmission intensity effects in the shadow image, as discussed in connection with FIGs.7, and 9.
  • FIG. 11 illustrates one exemplary method 1100 for detecting nanoparticles of interest in a shadow image such as the shadow image generated by method 1000.
  • Method 1100 is an embodiment of step 530 (FIG. 5).
  • Method 1100 may be performed by imaging system 900 (FIG. 9).
  • Step 1110 nanoparticles of interest are detected in the shadow image using Al.
  • Step 1110 includes steps 1120 to use Al instructions to detect nanoparticles of interest in the shadow images.
  • processor 312 (FIGs.5 and 9) executes shadow image analysis using Al instructions 920 in SD card 308 to identify shadows in a shadow image received from imaging system 700 (FIGs.7 and 9).
  • shadow image analysis using Al instructions 920 include Al algorithms, such as Tensorflow and Lite tensorflow algorithms.
  • geometrical criteria are invoked to identify shadows associated with nanoparticles of interest.
  • processor 312 utilizes automatic nanoparticles geometric criteria analysis 940 (FIG.
  • Step 1130 includes steps 1140 and 1150 of invoking size criteria and shape criteria, respectively.
  • processor 312 retrieves size criteria and shape criteria from automatic nanoparticles geometric criteria analysis 940 using Al instructions 920 to identify shadows associated with nanoparticles of interest.
  • Al was used to identify unknown nanoparticles or virus based on their predefined shape and size that are correlated with actual shape and size of nanoparticles or viruses captured by image sensor.
  • RNA and DNA features are invoked to identify shadows associated with unknown nanoparticles.
  • Step 1160 includes steps 1170 and 1180 of invoking RNA and DNA sequences for unknown nanoparticles, respectively.
  • processor 312 utilizes automatic nanoparticles RNA and DNA analysis 950 (FIG. 9) to identify the RNA and DNA sequences for unknown nanoparticles using its predefined RNA and DNA models created by Al instructions 920.
  • Al instructions 920 are used to correlate the predefined RNA and DNA sequences with the RNA and DNA sequences nanoparticles captured by imaging system 700 (FIG. 7).
  • FIG. 12 illustrates one exemplary imaging device 1200 configured for lens -free fluorescence imaging of a sample deposited on thin metal-film (Au-coated coverslip) used to image the sample.
  • Imaging system 1200 is an embodiment of thin metal-film 105 (FIGs.l, 2A, and 2B) tailored for fluorescence imaging.
  • Imaging system 1200 includes Au-coated coverslip 1210 disposed on image sensor 106 (FIGs.l, 2A, and 2B).
  • Au-coated coverslip 1210 is an embodiment of thin metal-film 105 (FIGs.l, 2A, and 2B).
  • FIG. 12 depicts imaging system 1200 in the same cross-sectional view as used in FIG. 2B for thin metal-film 105.
  • Au-coated coverslip 1210 includes Quartz layer 201, Ti layer 202, Au layer 1203 with thickness 10 nm, and SiO2 layer 204, respectively, of FIGs.2B, and 7.
  • FIG. 12 further illustrates the structure of imaging system 1200, which includes fluorescently labelled nanoparticle 1220.
  • Fluorescently labelled nanoparticles 1220 can be used to enhance the SEF of Au-coated coverslip by considering the effects of (a) Au-coated substrate thickness, (b) the spacer distance or SiO2 layer 204 thickness, (c) the illumination angle (0) 101, and (d) the excitation polarization and wavelength of UV light source 102. By adjusting all these factors pixel array of image sensor 106, can detect fluorescence emission from a fluorescently labelled nanoparticle located on Au-coated coverslip 1210.
  • Au-coated coverslip 1210 generates the maximum fluorescence image of fluorescently labelled nanoparticles on pixel array of image sensor 106. This allows for identification of fluorescently labelled nanoparticles of interest based upon fluorescence detection and the size and shape of the fluorescence event in the fluorescence image generated by Au-coated coverslip 1210 and image sensor 106. For example, fluorescently labelled nanoparticles of interest may be found as a subset of detected fluorescence events that further meet specified size criteria. Other geometrical criteria such as shape may be utilized as well for identification of fluorescently labelled nanoparticles of interest.
  • FIG. 13 illustrates one exemplary lens-free imaging system 1300 for detecting nanoparticles, which utilizes lens-free fluorescence imaging of a sample deposited on the Au-coated coverslip (FIG. 12) to create SEF used to generate fluorescence image(s) and capture the fluorescence image(s) using image sensor (FIG. 12).
  • Lens-free imaging system 1300 is an embodiment of imaging system 100 (FIG. 1) like imaging system 400 (FIG. 4) and imaging system 900 (FIG. 9).
  • imaging system 1300 includes imaging system 1200 (FIG. 12) instead imaging system (FIGs.l, and 4), and includes Au-coated coverslip 1210 and Au-coated coverslip SEF analysis 1301.
  • Simulation of SPP properties of Au-coated coverslip was performed using a finite-difference time-domain (FDTD) solution package (Lumerical). Each simulation consisted of Perfectly Matched Layer (PML) boundaries for 3nm Ti layer 202 on Quartz layer 201 and SiO2 layer 204 thickness of 0 to 50nm with 5nm step size on top of the Au layer 1203 (FIG. 12), followed by p-polarized (i.e., parallel to the plane of incidence) excitation UV light source 102 with a wavelength of 470-630 nm, which was launched from Quartz. An incidence angle 0 lOlsweep of 0 to 75° was performed for each SiO2 layer 204 thickness. The transmission intensity and the electrical field distribution at the SiO2/air interface above the Au layer 1203 were recorded. As for the refractive index values of different materials used in the simulation, material properties were adopted. Imaging system 1300, also, includes Al instructions 1320 inside SD card 1310.
  • Al Instructions 1320 includes automatic nanoparticles geometric analysis 1330 using DL of Al, automatic nanoparticles RNA and DNA modelling and analysis 1340 using DL of Al in SD card 1310, and unknown nanoparticles detection using the predefined RNA and DNA sequences model 1350 that, when executed by processor 312, Al instructions 1320 identify known and unknown nanoparticles of interest in shadow images generated by Au-coated coverslip and imaging sensor system 1200 and correlate shape and size or RNA and DNA sequences detected from fluorescence image with the predefined shape and size criteria 1330 or RNA and DNA sequences 1350.
  • Processor 312 retrieves geometric criteria 1330 or RNA and DNA sequences and model 1350 to identify known and unknown nanoparticles of interest based upon its geometric criteria or RNA and DNA sequences properties, respectively, from fluorescence events in fluorescence images generated by imaging system 1200 and correlated with the predefined geometric criteria 1330 or RNA and DNA sequences 1350.
  • FIG. 14 illustrates one exemplary method 1400 for lens free fluorescence imaging, using Au-coated film and imaging sensor, of a sample deposited on the Au-coated film.
  • Method 1400 is an embodiment of step 520 of method 500 (FIG. 5) and may be performed by imaging system 1300 (FIG. 13).
  • a step 1410 Au- coated-film to generate SEF for a fluorescence image of a sample, excited by UV light source to create SPP, located on the SiO2 layer 204 and disposed on the pixel array of the imaging sensor.
  • Step 1410 includes steps 1420 and 1430.
  • the sample is excited by fluorescence excitation light to create SPP.
  • UV light source 102 (FIGs.l and 13) generates illumination to illuminate the sample (FIG. 12).
  • Sample 1220 (FIG. 12) is, for example, a human blood sample with one or more types of nanoparticles specifically labelled with fluorescent labels.
  • step 1430 light transmitted by a fluorescence emission is detected using a photosensitive pixel array of the imaging sensor. This transmitted light is including fluorescence emission.
  • pixel array in imaging sensor 106 (FIG. 12) detects fluorescence emission.
  • step 1430 includes a step 1440 of performing the detection at an acceptance angle and distance from SiO2 layer 204 to the photosensitive pixel array in imaging sensor 106 that increases transmitted intensity in the fluorescence image, as discussed in connection with FIG. 12. In the embodiment, step 1430 is performed after step 1420.
  • FIG. 15 illustrates one exemplary method 1500 for detecting nanoparticles of interest in a fluorescence image.
  • Method 1500 is an embodiment of step 530, and 540 (FIG. 5).
  • Method 1500 is performed, for example, by lens-free imaging system 1300 (FIG. 13).
  • a step 1510 nanoparticles of interest are detected in the fluorescence image.
  • Step 1510 includes a step 1520, 1530, an optional steps 1560 and 1570.
  • fluorescence events are identified in the fluorescence image using Al algorithm.
  • processor 312 executes fluorescence image analysis using Al instructions 1320 to identify fluorescence events in a fluorescence image created by Au-coated film and received from imaging system 1200 and 1300 (FIGs.12 and 13).
  • fluorescence image analysis using Al instructions 1320 include algorithms such as Tensorflow and Lite Tensorflow.
  • geometries criteria are invoked to identify fluorescence events associated with nanoparticles of interest.
  • processor 312 performs one or both of steps 1540 and 1550 to identify fluorescence events associated with nanoparticles of interest.
  • Al was used to identify unknown nanoparticles or virus based on their predefined shape and size that are correlated with actual shape and size of nanoparticles or viruses of interest in fluorescence image captured by image sensor.
  • step 1540 Al was used to extract nanoparticles size features 1540 are invoked to identify the nanoparticles size based on SEF and using Al algorithms.
  • processor 312 utilizes automatic nanoparticles geometric criteria 1330 (FIG. 13) to identify the size based on Al and SEF fluorescence events associated with nanoparticles of interest and, potentially, reject fluorescence events not associated with nanoparticles size of interest.
  • step 1550 Al was used to extract nanoparticles shape features 1550 are invoked to identify the nanoparticles shape based on SEF and using Al algorithms.
  • processor 312 utilizes automatic nanoparticles geometric criteria 1330 (FIG. 13) to identify the shape based on Al and SEF fluorescence events associated with nanoparticles of interest and, potentially, reject fluorescence events not associated with nanoparticles shape of interest.
  • RNA and DNA features are invoked to identify fluorescent events associated with nanoparticles of interest using Al.
  • processor 312 utilizes automatic nanoparticles RNA and DNA analysis 1340 (FIG. 13) to identify the RNA and DNA sequences and modelling of nanoparticles.
  • step 1561 and 1562 are invoked to identify the fluorescent events of RNA and DNA respectively using DL of Al.
  • step 1570 includes steps 1571 and 1572 of invoking RNA and DNA sequences for unknown nanoparticles based on the predefined RNA and DNA sequences in Al, respectively.
  • processor 312 retrieves RNA and DNA sequences from automatic nanoparticles RNA and DNA features analysis 1350 using Al instructions 1320 to identify RNA and DNA sequences associated with unknown nanoparticles of interest using.
  • This device has many features that can be used in many applications. These features include:
  • This device is a lens-free imaging system equipped with thin metal-film and Al for detecting nanoparticles (such as virus) in a sample deposited on gold coated coverslip for holding a sample and create SEF to generate shadow image that generate SPP when it excited by UV light source, and an image sensor for capture the sample shadow image.
  • nanoparticles such as virus
  • the imaging device denoted as (Cl) includes UV light source for exciting the sample to generate SPP to form an image of the nanoparticles.
  • the imaging device denoted as (Cl) through (C2) further includes thin metal-film including four layers starting from Quartz with 10 nm, Ti with 3 nm, Au with 10 nm, and SiO2 with 15 nm.
  • the imaging device denoted as (Cl) through (C3) includes controller with its components to detect and control images that are created by lens-free image system and thin metal-film.
  • the imaging device denoted as (Cl) through (C4) includes SEF and transmission effects of thin metal-film for air and a sample deposited on the thin metal-film used to image the sample.
  • the imaging device denoted as (Cl) through (C5) includes SEF and transmission effects for a plane wave of light incident on SiO2 layer of thin metal-film.
  • the imaging device denoted as (Cl) through (C6) includes SEF, transmission, absorption, and reflection effects for a plane wave of UV light incident on Ti layer of thin metal-film.
  • the imaging device denoted as (Cl) through (C7) includes SEF, transmission, absorption, and reflection effects for a plane wave of UV light incident on Au layer of thin metal-film.
  • the imaging device denoted as (Cl) through (C8) includes lens-free imaging equipped with thin metal-film and Al method for detecting nanoparticles based on their geometrical features, RNA, and DNA in a sample deposited on the thin metal-film in a shadow image.
  • the imaging device denoted as (Cl) through (C9) includes lens-free fluorescence imaging of nanoparticles such as viruses in a sample deposited on the thin metal-film used to image the sample.
  • the lens-free imaging device denoted as (Cl) through (CIO) includes lens-free imaging system equipped with thin metal-film and Al for detecting unknown nanoparticles such as viruses in a sample deposited on the thin metal-film.
  • (Cl 2) The imaging device denoted as (Cl) through (Cl l) lens-free imaging equipped with thin metalfilm and Al for performing lens-free fluorescence imaging, using an image sensor, thin metal-film and Al, of unknown nanoparticles such as viruses in a sample deposited on the thin metal-film.
  • the new non-invasive device is based on a lens-free imaging system equipped with thin metal-film and Al for detecting nanoparticles (such as virus) in a sample deposited on gold coated coverslip includes a thin metal-film for holding a sample and create shadow image and an image sensor for imaging and capture the sample shadow image is sufficient to detect and predict known and unknown virus.
  • This device enables continuous virus mentoring, detection, prediction, and blood test without using invasive tools.
  • the device has been tailored and designed to perform multiple purposes and satisfy the unmet market needs such as:
  • DI People and Animals Virus Detection: This device addresses the need for virus detection in conditions resulting in patient immobilization for greater than two weeks or more, or virus detection where the patient is immobilized indefinitely.
  • SUBSTITUTE SHEET (RULE 26) In animal models, this device can easily detect virus in animals such as Monkey or Bat that caused CO VID- 19 infection in people.
  • the device is well-designed to use in human and animal to send the results automatically using Al algorithms.
  • the present invention represents a non-invasive device to detect known and unknown viruses in health sectors such as Pharma, Hospitals, and Laboratories. Also, the present invention can modify to scan complete blood count (CBC) by reconfiguring the Al modules and using the novel UV light source with the lens-free imaging platform.
  • CBC complete blood count
  • This device can be used for cancer, HIV diagnosis, and environment DNA (eDNA) analysis, and forensic.

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Abstract

L'invention concerne un système d'imagerie destiné à détecter des nanoparticules ou des virus, comprenant : un film métallique mince éclairé par une source de lumière ultraviolette pour générer une fluorescence exaltée en surface afin d'améliorer la sensibilité de détection et maintenir un échantillon qui est excité par une lumière transmise à partir du film métallique mince pour générer des plasmon-polaritons de surface en vue de créer une image de fluorescence de nanoparticules, le film métallique mince étant déposé directement sur des pixels photosensibles du capteur d'image utilisé pour capturer une image de fluorescence, et l'IA intégrée dans le contrôleur pour détecter des nanoparticules. De nouveaux modèles d'IA sont développés pour modéliser des caractéristiques de géolocalisation, de l'acide ribonucléique et de l'acide désoxyribonucléique de virus et corréler ses données réelles avec des caractéristiques de virus extraites à partir d'ensembles de données prédéfinis de virus pour détecter automatiquement des virus connus et inconnus. Un procédé de détection de nanoparticules dans un échantillon déposé sur un film métallique mince comprend (a) la génération d'une fluorescence exaltée en surface et de plasmon-polaritons de surface à l'aide d'un film métallique mince pour créer une image de fluorescence améliorée, et (b) la détection de virus connus et inconnus dans l'échantillon à l'aide de l'IA.
PCT/AU2021/051240 2020-10-29 2021-10-26 Outil intelligent non invasif pour la surveillance continue de virus et la détection rapide de virus connus et inconnus WO2022087657A1 (fr)

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Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20130193544A1 (en) * 2010-10-18 2013-08-01 The Regents Of The University Of California Microscopy method and system incorporating nanofeatures
US20140045730A1 (en) * 2011-04-05 2014-02-13 Integrated Plasmonics Corporation Integrated plasmonic sensing device and apparatus
US20150338402A1 (en) * 2014-05-22 2015-11-26 The University Of Maryland, Baltimore Tamm Structures for Enhanced Fluorescence Based Sensing, Imaging and Assays

Patent Citations (3)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US20130193544A1 (en) * 2010-10-18 2013-08-01 The Regents Of The University Of California Microscopy method and system incorporating nanofeatures
US20140045730A1 (en) * 2011-04-05 2014-02-13 Integrated Plasmonics Corporation Integrated plasmonic sensing device and apparatus
US20150338402A1 (en) * 2014-05-22 2015-11-26 The University Of Maryland, Baltimore Tamm Structures for Enhanced Fluorescence Based Sensing, Imaging and Assays

Non-Patent Citations (1)

* Cited by examiner, † Cited by third party
Title
HWANG, E. ET AL.: "Surface Plasmon Polariton Enhanced Fluorescence from Quantum Dots on Nanostructured Metal Surfaces", AMERICAN CHEMICAL SOCIETY NANO LETTERS, vol. 10, no. 3, 29 January 2010 (2010-01-29), pages 813 - 820, XP055151025, DOI: 10.1021/nl9031692 *

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