A bacterial autofluorescence-based bone infection image acquisition method and system

Abstract

The application discloses a kind of bone infection image acquisition method and system based on bacterial autofluorescence.The bone infection image acquisition method based on bacterial autofluorescence includes: obtaining the binary mask and three-dimensional topographic model of the tissue to be measured;According to the three-dimensional topographic model of the tissue to be measured, illumination correction chart and collection correction chart are generated;Control light source module to the tissue to be measured Time emission first wavelength fluorescence, utilize light field modulation module based on illumination correction chart to modulate illumination light field, time acquisition first wavelength and second wavelength fluorescence corresponding fluorescence image, and generate background fluorescence image (for first wavelength) and total fluorescence image (for second wavelength);According to total fluorescence image and background fluorescence image, bacterial fluorescence image is generated.The application eliminates the light intensity error caused by distance and angle through three-dimensional topographic correction, and significantly reduces the interference of tissue background fluorescence through double-wavelength difference strategy, improves the imaging quality.

Description

Technical Field

[0001] This invention relates to the field of biomedical optical detection technology, and in particular to a method and system for acquiring bone infection images based on bacterial autofluorescence. Background Technology

[0002] Postoperative wound infection following orthopedic surgery (such as internal fixation of fractures and joint replacement) is a significant complication leading to surgical failure, chronic osteomyelitis, and even amputation. Currently, clinical diagnosis of orthopedic infections relies primarily on visual inspection, body temperature, white blood cell count, and bacterial culture. However, visual assessment is highly subjective and has low sensitivity; while bacterial culture is the "gold standard," it takes 24 to 72 hours, failing to meet the needs for early intervention.

[0003] In recent years, studies have found that many pathogenic bacteria (such as Staphylococcus aureus and Pseudomonas aeruginosa) can produce characteristic autofluorescence under ultraviolet light excitation at specific wavelengths, allowing them to be detected without external staining. For example, under 405 nm excitation, porphyrins produced by bacteria emit red fluorescence at 600-665 nm, while the background fluorescence of tissue is weak.

[0004] Based on this, existing technologies have provided a handheld fluorescence imaging device for bone infection image acquisition. However, existing technologies do not consider the influence of the three-dimensional morphology of the wound on the uniformity of illumination, which leads to the fluorescence intensity being affected by distance and angle, making it difficult to complete bacterial load analysis. Furthermore, existing technologies lack an effective tissue background fluorescence suppression mechanism, causing confusion between tissue background fluorescence and bacterial fluorescence. Summary of the Invention

[0005] In view of the above problems, the present invention is proposed to provide a method and system for acquiring bone infection images based on bacterial autofluorescence that overcomes or at least partially solves the above problems.

[0006] One embodiment of the present invention provides a method for acquiring bone infection images based on bacterial autofluorescence, the method comprising: The light source module emits white light to the tissue under test, and acquires a diffuse reflection image of the white light to obtain a binary mask of the tissue under test. Continue to control the light source module to emit white light to the tissue under test, and use the light field modulation module to generate structured light, acquire the structured light diffuse reflection image, calculate the three-dimensional height distribution of the tissue under test based on the phase unfolding algorithm, and obtain the three-dimensional morphology model of the tissue under test based on the binary mask of the tissue under test and the three-dimensional height distribution of the tissue under test. Based on the three-dimensional morphology model of the tissue under test, illumination correction map and collection correction map are generated according to Lambert's cosine law and inverse square law. The control light source module emits fluorescence of a first wavelength to the tissue under test. The light field modulation module modulates the illumination light field based on the illumination correction map, collects the fluorescence image corresponding to the first wavelength of fluorescence, and generates a background fluorescence image based on the binary mask of the tissue under test and the collection correction map. The control light source module emits fluorescence of a second wavelength to the tissue under test. The light field modulation module modulates the illumination light field based on the illumination correction map, collects the fluorescence image corresponding to the second wavelength fluorescence, and generates a total fluorescence image based on the binary mask of the tissue under test and the collection correction map. A difference image is calculated based on the total fluorescence image and the background fluorescence image, and the difference image is used as the bacterial fluorescence image; Wherein, the first wavelength is shorter than the second wavelength, the fluorescence of the first wavelength is used to excite the tissue background fluorescence, and the fluorescence of the second wavelength is used to simultaneously excite the tissue background fluorescence and the bacterial characteristic fluorescence.

[0007] Optionally, the first wavelength is 365nm-385nm, and the second wavelength is 395nm-415nm.

[0008] Optionally, the step of generating illumination correction maps and collection correction maps based on the three-dimensional morphology model of the tissue under test using Lambert's cosine law and inverse square law includes generating illumination correction maps and collection correction maps according to the following formulas: in, The spatial coordinates of each point on the surface of the tissue to be tested. For lighting calibration diagram, To collect calibration images, The distance from the light source module to the surface of the tissue being measured. The angle of incidence from the light source module to the surface of the tissue being tested. This indicates the distance from the imaging lens to the surface being measured. The angle at which the imaging lens receives the reflected light from the tissue under test.

[0009] Optionally, generating a background fluorescence image based on the binary mask of the tissue to be tested and the collection correction map includes: The fluorescence image corresponding to the first wavelength is multiplied by the binary mask of the tissue under test and the collection correction image to generate a background fluorescence image.

[0010] Optionally, generating a total fluorescence image based on the binary mask of the tissue to be tested and the collection calibration map includes: The fluorescence image corresponding to the second wavelength is multiplied by the binary mask of the tissue under test and the collection correction image to generate the total fluorescence image.

[0011] Optionally, the method further includes: controlling the polarization module and the polarization detection module to be orthogonally configured.

[0012] Another embodiment of the present invention provides a bone infection image acquisition system based on bacterial autofluorescence. This system performs the above-described bone infection image acquisition method based on bacterial autofluorescence. The system includes: The light source module integrates three LEDs for time-division multiplexing of white light, fluorescence of a first wavelength, and fluorescence of a second wavelength; The light field modulation module is used to generate uniform illumination light fields or sinusoidal / Gray code structured light; The projection lens, located at the rear end of the light field modulation module, is used to project the modulated light field onto the surface of the tissue to be tested. A filter switching device for switching between narrowband fluorescent filters and full-transmission filters; An imaging lens is used to focus the light signal from the tissue being tested. The image acquisition module is used to acquire white light images, fluorescence images corresponding to the first wavelength of fluorescence, and fluorescence images corresponding to the second wavelength of fluorescence in a time-division manner. Drive control module: used to drive and control the light source module, the light field modulation module and the filter switching device to realize light source switching, structured light projection and filter switching; The data analysis and processing module is used to process the white light image, the fluorescence image corresponding to the first wavelength of fluorescence, and the fluorescence image corresponding to the second wavelength of fluorescence acquired by the image acquisition module.

[0013] Optionally, it also includes: A polarization module, located at the rear end of the projection lens, is used to generate linearly polarized excitation light; The polarization detection module is located at the front end of the imaging lens, and its polarization direction is orthogonal to the polarization induction module.

[0014] Optionally, the light field modulation module employs a digital micromirror device or a liquid crystal spatial light modulator.

[0015] Optionally, the image acquisition module includes a CCD sensor, a CMOS sensor, or an sCMOS sensor.

[0016] Another embodiment of the present invention provides an electronic device, wherein the electronic device includes: Processor; and, A memory is configured to store computer-executable instructions, which, when executed, cause the processor to perform the aforementioned bone infection image acquisition method based on bacterial autofluorescence.

[0017] Another embodiment of the present invention provides a computer-readable storage medium storing one or more programs that, when executed by a processor, implement the above-described method for acquiring bone infection images based on bacterial autofluorescence.

[0018] The beneficial effects of this invention are that it eliminates light intensity errors caused by distance and angle through three-dimensional morphology correction, and significantly reduces tissue background fluorescence interference through a dual-wavelength difference strategy, thereby improving imaging quality and providing a high-quality image foundation for subsequent bacterial load analysis. This invention is contactless, requires no labeling, sampling, or staining, and can efficiently and conveniently complete image acquisition.

[0019] Furthermore, this invention effectively suppresses specular reflection through a cross-polarization design, improving the fluorescence signal-to-noise ratio. This invention can also be used to register white light images with bacterial fluorescence images to generate pseudo-color bacterial distribution maps, facilitating intuitive viewing for doctors and assisting them in identifying bone infection areas. Attached Figure Description

[0020] Figure 1 This is a flowchart of a bone infection image acquisition method based on bacterial autofluorescence according to an embodiment of the present invention; Figure 2 This is a schematic diagram illustrating the principle of three-dimensional topography correction according to an embodiment of the present invention. Figure 3 This is a schematic diagram of a bone infection image acquisition system based on bacterial autofluorescence, according to an embodiment of the present invention. Figure 4 A flowchart illustrating another embodiment of the bone infection image acquisition method based on bacterial autofluorescence of the present invention; Figure 5 This is a schematic diagram of another embodiment of the present invention: a bone infection image processing method based on bacterial autofluorescence. Detailed Implementation

[0021] In orthopedic surgery and wound management, rapid and accurate identification of bacterial distribution is crucial for determining the extent of debridement. Bacteria (such as Staphylococcus aureus and Pseudomonas aeruginosa) produce characteristic autofluorescence (mainly porphyrins) under ultraviolet light excitation at specific wavelengths, while surrounding healthy tissue produces weak background autofluorescence. Utilizing this characteristic for label-free imaging has become a research hotspot.

[0022] However, existing image acquisition technologies have significant technical bottlenecks: Light intensity distortion caused by three-dimensional morphology: Orthopedic wounds are usually irregular three-dimensional curved surfaces. Due to differences in distance from the light source / camera and surface normal angles at different locations on the wound, even with the same bacterial load, the fluorescence intensity collected can vary greatly (the error can be several to tens of times). This makes traditional two-dimensional fluorescence images unable to accurately reflect the bacterial load, which can easily lead to misjudgment.

[0023] Limitations of post-processing correction: Existing technologies mostly use the method of "first acquiring uneven images, and then multiplying them by correction coefficients through software algorithms" for compensation. However, for dark areas with insufficient lighting, software gain will amplify both the signal and noise, resulting in a sharp drop in signal-to-noise ratio (SNR). For bright areas with excessive lighting, the information loss caused by pixel saturation cannot be recovered by algorithms.

[0024] Severe environmental interference: The moist bone tissue surface produces specular reflection, masking weak bacterial fluorescence signals.

[0025] Therefore, there is an urgent need for an image acquisition method and system that can actively compensate for geometric attenuation from the light source end, uniformly excite the light field, and combine multi-wavelength differential and polarization suppression techniques to achieve high signal-to-noise ratio and high-precision quantitative image acquisition.

[0026] To make the objectives, technical solutions, and advantages of the present invention clearer, the embodiments of the present invention will be described in further detail below with reference to the accompanying drawings.

[0027] Figure 1 This is a flowchart illustrating a bone infection image acquisition method based on bacterial autofluorescence, according to an embodiment of the present invention. Figure 1 As shown, the method includes: S101: Control the light source module to emit white light to the tissue under test, acquire the diffuse reflection image of white light, and obtain the binary mask of the tissue under test; S102: Continue to control the light source module to emit white light to the tissue under test, and use the light field modulation module to generate structured light, acquire the structured light diffuse reflection image, calculate the three-dimensional height distribution of the tissue under test based on the phase unfolding algorithm, and obtain the three-dimensional morphology model of the tissue under test according to the binary mask of the tissue under test and the three-dimensional height distribution of the tissue under test. It should be noted that, in this embodiment of the invention, the control light field modulation module loads the illumination correction map and spatially modulates the light field intensity of the excitation light. This ensures that when the modulated excitation light is projected onto the target area, it compensates for the attenuation caused by distance and angle, making the actual excitation light power received at each point in the target area more consistent. This embodiment of the invention results in highly uniform raw images, avoiding the amplification of noise by post-processing algorithms.

[0028] S103: Based on the three-dimensional morphology model of the tissue to be tested, generate an illumination correction map and a collection correction map according to Lambert's cosine law and the inverse square law; S104: The control light source module emits fluorescence of the first wavelength to the tissue under test, the light field modulation module modulates the illumination light field based on the illumination correction map, the fluorescence image corresponding to the first wavelength fluorescence is collected, and a background fluorescence image is generated according to the binary mask of the tissue under test and the collection correction map. S105: The control light source module emits fluorescence of the second wavelength to the tissue under test, the light field modulation module modulates the illumination light field based on the illumination correction map, the fluorescence image corresponding to the second wavelength fluorescence is collected, and the total fluorescence image is generated according to the binary mask of the tissue under test and the collection correction map. S106: Calculate a difference image based on the total fluorescence image and the background fluorescence image, and use the difference image as the bacterial fluorescence image; Wherein, the first wavelength is shorter than the second wavelength, the fluorescence of the first wavelength is used to excite the tissue background fluorescence, and the fluorescence of the second wavelength is used to simultaneously excite the tissue background fluorescence and the bacterial characteristic fluorescence.

[0029] This invention eliminates light intensity errors caused by distance and angle through three-dimensional morphology correction, and significantly reduces tissue background fluorescence interference through a dual-wavelength differential strategy, thereby improving imaging quality and providing a high-quality image foundation for subsequent bacterial load analysis. This invention is contactless, requires no labeling, sampling, or staining, and enables efficient and convenient image acquisition.

[0030] In practical applications, the first wavelength is 365nm-385nm, and the second wavelength is 395nm-415nm.

[0031] Figure 2 This is a schematic diagram illustrating the principle of three-dimensional topography correction according to an embodiment of the present invention. Figure 2 As shown, the step of generating illumination correction maps and collection correction maps based on the three-dimensional morphology model of the tissue under test using Lambert's cosine law and inverse square law includes generating illumination correction maps and collection correction maps according to the following formulas: in, The spatial coordinates of each point on the surface of the tissue to be tested. For lighting calibration diagram, To collect calibration images, The distance from the light source module to the surface of the tissue being measured. The angle of incidence from the light source module to the surface of the tissue being tested. This indicates the distance from the imaging lens to the surface of the tissue being tested. The angle at which the imaging lens receives the reflected light from the tissue under test.

[0032] Specifically, generating a background fluorescence image based on the binary mask of the tissue to be tested and the collection correction map includes: The fluorescence image corresponding to the first wavelength is multiplied by the binary mask of the tissue under test and the collection correction image to generate a background fluorescence image.

[0033] Specifically, generating the total fluorescence image based on the binary mask of the tissue to be tested and the collection correction map includes: The fluorescence image corresponding to the second wavelength is multiplied by the binary mask of the tissue under test and the collection correction image to generate the total fluorescence image.

[0034] In an optional embodiment of the present invention, the method further includes: controlling the polarization module and the polarization detection module to be orthogonally configured. Cross-polarization design can effectively suppress specular reflection and improve the fluorescence signal-to-noise ratio.

[0035] Preferably, the method further includes: registering the white light image with the bacterial fluorescence image to generate a pseudo-color bacterial distribution map, which is convenient for doctors to view intuitively and assists doctors in judging the bone infection area.

[0036] Figure 3 This is a schematic diagram of a bone infection image acquisition system based on bacterial autofluorescence, according to an embodiment of the present invention. The system performs the aforementioned bone infection image acquisition method based on bacterial autofluorescence, as follows: Figure 3 As shown, the system includes: The light source module 301 integrates three LEDs for time-division multiplexing of white light, fluorescence of a first wavelength, and fluorescence of a second wavelength; The first wavelength of fluorescence is used to excite the background fluorescence of the tissue, and the second wavelength is used to excite the characteristic fluorescence of the bacteria. The white light covers the 420–700 nm band for high-fidelity tissue structure imaging. All three LEDs are controlled by independent constant current drive circuits, supporting precise adjustment of light intensity.

[0037] The light field modulation module 302 is used to generate a uniform illumination light field or sinusoidal / Gray code structured light. The projection lens 303 is located at the rear end of the light field modulation module and is used to project the modulated light field onto the surface of the tissue to be tested. The filter switching device 306 is used to switch between a narrowband fluorescent filter and a full-transmission filter; Understandably, the filter switching device 306 includes an electric filter wheel that can switch between a narrowband fluorescence filter (for fluorescence imaging) and a fully transmissive filter (for white light imaging).

[0038] Imaging lens 307 is used to focus the light signal of the tissue to be tested; In practical applications, the imaging lens 307 adopts a low-distortion, high-transmittance apochromatic lens.

[0039] The image acquisition module 308 is used for time-division acquisition of white light images, fluorescence images corresponding to the first wavelength of fluorescence, and fluorescence images corresponding to the second wavelength of fluorescence; In practical applications, the image acquisition module 308 uses a scientific / industrial grade camera, which has high quantum efficiency and low noise characteristics.

[0040] Drive control module 309: used to drive and control the light source module, the light field modulation module and the filter switching device to realize light source switching, structured light projection and filter switching; The data analysis and processing module 310 is used to process the white light image, the fluorescence image corresponding to the first wavelength fluorescence, and the fluorescence image corresponding to the second wavelength fluorescence acquired by the image acquisition module.

[0041] This invention eliminates light intensity errors caused by distance and angle through three-dimensional morphology correction, and significantly reduces tissue background fluorescence interference through a dual-wavelength differential strategy, thereby improving imaging quality and providing a high-quality image foundation for subsequent bacterial load analysis. This invention is contactless, requires no labeling, sampling, or staining, and enables efficient and convenient image acquisition.

[0042] In an optional embodiment of the present invention, the system further includes: The polarization module 304 is disposed at the rear end of the projection lens and is used to generate linearly polarized excitation light; The polarization analyzer module 305 is disposed at the front end of the imaging lens, and its polarization direction is orthogonal to the polarization initiator module.

[0043] In practical applications, the polarization module 304 is composed of a high extinction ratio linear polarizer. The polarization module 304 and the polarization analyzer module 305 form a cross-polarization optical path, which effectively suppresses specular reflection.

[0044] In practical applications, the light field modulation module 302 uses a digital micromirror device (DMD) or a liquid crystal spatial light modulator (SLM).

[0045] Preferably, the image acquisition module 308 includes a CCD sensor, a CMOS sensor, or an sCMOS sensor.

[0046] It should be noted that traditional CCD sensors have low frame rates and cannot achieve rapid multi-wavelength switching for acquisition, while ordinary CMOS sensors have high noise and cannot acquire weak fluorescence. The sCMOS in this embodiment achieves the best balance between signal-to-noise ratio and speed, and is the key hardware configuration for achieving real-time image acquisition in this embodiment.

[0047] Figure 4 This is a flowchart of a bone infection image acquisition method based on bacterial autofluorescence, according to another embodiment of the present invention. Figure 5 This is a schematic diagram illustrating the principle of a bone infection image processing method based on bacterial autofluorescence, according to another embodiment of the present invention. Figure 4 and Figure 5 In the embodiment, the first wavelength is 375nm and the second wavelength is 405nm. This wavelength setting can most accurately remove background fluorescence interference.

[0048] Step 1: Intelligent segmentation of the tissue region to be tested The white LED is lit, and the light field modulation module generates a uniform illumination field. The polarization module and the polarization analyzer are orthogonally configured to suppress specular reflection. The image acquisition module acquires high-contrast diffuse reflection images of the white light. The data analysis and processing module automatically identifies and segments the tissue region to be tested using a built-in image segmentation algorithm (such as the U-Net segmentation network algorithm) or a pre-trained deep learning model, generating a binary mask. It is used to remove background interference.

[0049] In practical applications, a uniform illumination field is generated by dynamically modulating the LED driving current or the DMD micromirror angle.

[0050] Step 2: 3D topography model Generate and calculate lighting correction diagrams and collect calibration charts .

[0051] Maintaining white light illumination and orthogonal polarization configuration, the light field modulation module projects phase-shifted sinusoidal or Gray code structured light; the image acquisition module acquires deformed fringe images; and the data analysis and processing module uses a phase unfolding algorithm to calculate the three-dimensional height distribution of the target area. and with Multiply to obtain a three-dimensional topographic model containing only the tissue under test. .

[0052] Based on the spatial geometric relationship between the light source, camera, and tissue surface, and combined with a three-dimensional morphology model, the illumination intensity attenuation factor (determined by the inverse square ratio of distance and the cosine of the incident angle) and the collection intensity attenuation factor (determined by the detection distance and the receiving angle) at each pixel are calculated to generate an illumination correction map. With collection and correction diagram .

[0053] in, The spatial coordinates of each point on the surface of the tissue to be tested. For lighting calibration diagram, To collect calibration images, The distance from the light source module to the surface of the tissue being measured. The angle of incidence from the light source module to the surface of the tissue being tested. This indicates the distance from the imaging lens to the surface being measured. The angle at which the imaging lens receives the reflected light from the tissue under test.

[0054] Step 3: 375 nm background fluorescence image generate Lighting up a 375 nm LED, utilizing The illumination field is modulated to make the actual excitation light power received at various points on the tissue surface tend to be consistent; fluorescence images are acquired and compared with... Multiply by, then multiply by The corrected background fluorescence image was obtained. .

[0055] Step 4: Total fluorescence image at 405 nm generate Similarly, by lighting a 405 nm LED, performing illumination modulation and image acquisition, and then performing masking and collection correction, the corrected total fluorescence image is obtained. This includes tissue background fluorescence and bacteria-specific fluorescence.

[0056] Calculate the difference image: Since 375 nm primarily excites tissue background fluorescence, while 405 nm excites both background and bacterial fluorescence, the subtraction of these two excitations effectively suppresses tissue autofluorescence interference. Ultimately, The gray value is directly proportional to the local bacterial load; the higher the value, the more severe the infection.

[0057] The following details the driving control process of the drive control module 309 for the light source module 301, the light field modulation module 302, and the filter switching device 306: (1) The drive control module 309 controls the light source module 301 to light up the white LED, controls the light field modulation module 302 to output a uniform light field, controls the filter switching device 306 to select a fully transmissive filter, and the uniform light field generates linearly polarized light through the polarizer module 304. The polarizer module 304 and the polarizer module 305 are perpendicular in the transmission direction. After the diffuse reflection light signal of the tissue under test passes through the polarizer module 305, the image is acquired by the image acquisition module 308, and the data analysis and processing module 310 performs image processing to generate a binary mask.

[0058] (2) The drive control module 309 controls the light source module 301 to light up the white LED, controls the light field modulation module 302 to output sinusoidal or Gray code structured light, controls the filter switching device 306 to select the full transmission filter, the structured light passes through the polarizer module 304 to generate linearly polarized light, the diffuse reflection light signal of the tissue under test passes through the polarization analyzer module 305 and the image is acquired by the image acquisition module 308, the data analysis and processing module 310 performs image processing to generate a three-dimensional morphological model of the tissue under test, and generates an illumination correction map and a collection correction map.

[0059] (3) The drive control module 309 controls the light source module 301 to light up the 375 nm LED, controls the light field modulation module 302 to output spatially modulated light using the illumination correction diagram, controls the filter switching device 306 to select the fluorescence filter, generates linearly polarized light through the polarization module 304, and the fluorescence signal of the tissue to be tested is collected by the image acquisition module 308 after passing through the polarization detection module 305. The image is then corrected using the collection correction diagram to obtain the fluorescence background image.

[0060] (4) The drive control module 309 controls the light source module 301 to light up the 405 nm LED, controls the light field modulation module 302 to output spatially modulated light using the illumination correction diagram, controls the filter switching device 306 to select the fluorescence filter, generates linearly polarized light through the polarizer module 304, and the fluorescence signal of the tissue to be tested is collected by the image acquisition module 308 after passing through the polarization detection module 305. The image is then corrected using the collection correction diagram to obtain the bacterial fluorescence image.

[0061] The present invention provides a method and system for acquiring bone infection images based on bacterial autofluorescence, which integrates structured light three-dimensional reconstruction, polarization imaging and multi-wavelength fluorescence differential technology. This invention can assist in the non-invasive detection of bone infection and is suitable for intraoperative real-time screening and postoperative dynamic monitoring in scenarios such as orthopedic surgical wounds, chronic osteomyelitis, and post-joint replacement infection.

[0062] It should be noted that: Numerous specific details are set forth in the specification provided herein. However, it will be understood that embodiments of the invention may be practiced without these specific details. In some instances, well-known methods, structures, and techniques have not been shown in detail so as not to obscure the understanding of this specification.

[0063] Similarly, it should be understood that, in order to simplify the invention and aid in understanding one or more of the various inventive aspects, in the above description of exemplary embodiments of the invention, various features of the invention are sometimes grouped together in a single embodiment, figure, or description thereof. However, this disclosure should not be construed as reflecting an intention that the claimed invention requires more features than are expressly recited in each claim. Rather, as reflected in the following claims, inventive aspects lie in fewer than all features of a single foregoing disclosed embodiment. Therefore, the claims following the detailed description are hereby expressly incorporated into this detailed description, wherein each claim itself is a separate embodiment of the invention.

[0064] Furthermore, those skilled in the art will understand that although some embodiments described herein include certain features included in other embodiments but not others, combinations of features from different embodiments are meant to be within the scope of the invention and form different embodiments.

[0065] The above description is merely a specific embodiment of the present invention. Under the teachings of the present invention, those skilled in the art can make other improvements or modifications based on the above embodiments. Those skilled in the art should understand that the above specific description is only to better explain the purpose of the present invention, and the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A method for acquiring bone infection images based on bacterial autofluorescence, characterized in that, The light source module emits white light to the tissue under test, and acquires a diffuse reflection image of the white light to obtain a binary mask of the tissue under test. Continue to control the light source module to emit white light to the tissue under test, and use the light field modulation module to generate structured light, acquire the structured light diffuse reflection image, calculate the three-dimensional height distribution of the tissue under test based on the phase unfolding algorithm, and obtain the three-dimensional morphology model of the tissue under test based on the binary mask of the tissue under test and the three-dimensional height distribution of the tissue under test. Based on the three-dimensional morphology model of the tissue under test, illumination correction map and collection correction map are generated according to Lambert's cosine law and inverse square law. The control light source module emits fluorescence of a first wavelength to the tissue under test. The light field modulation module modulates the illumination light field based on the illumination correction map, collects the fluorescence image corresponding to the first wavelength of fluorescence, and generates a background fluorescence image based on the binary mask of the tissue under test and the collection correction map. The control light source module emits fluorescence of a second wavelength to the tissue under test. The light field modulation module modulates the illumination light field based on the illumination correction map, collects the fluorescence image corresponding to the second wavelength fluorescence, and generates a total fluorescence image based on the binary mask of the tissue under test and the collection correction map. A difference image is calculated based on the total fluorescence image and the background fluorescence image, and the difference image is used as the bacterial fluorescence image; Wherein, the first wavelength is shorter than the second wavelength, the fluorescence of the first wavelength is used to excite the tissue background fluorescence, and the fluorescence of the second wavelength is used to simultaneously excite the tissue background fluorescence and the bacterial characteristic fluorescence.

2. The bone infection image acquisition method based on bacterial autofluorescence according to claim 1, characterized in that, The first wavelength is 365nm-385nm, and the second wavelength is 395nm-415nm.

3. The bone infection image acquisition method based on bacterial autofluorescence according to claim 1, characterized in that, The step of generating illumination correction maps and collection correction maps based on the three-dimensional morphology model of the tissue under test, using Lambert's cosine law and inverse square law, includes generating illumination correction maps and collection correction maps according to the following formulas: in, The spatial coordinates of each point on the surface of the tissue to be tested. For lighting calibration diagram, In order to collect calibration charts, The distance from the light source module to the surface of the tissue being measured. The angle of incidence from the light source module to the surface of the tissue being tested. This indicates the distance from the imaging lens to the surface of the tissue being tested. The angle at which the imaging lens receives the reflected light from the tissue under test.

4. The bone infection image acquisition method based on bacterial autofluorescence according to claim 1, characterized in that, The step of generating a background fluorescence image based on the binary mask of the tissue to be tested and the collection correction map includes: The fluorescence image corresponding to the first wavelength is multiplied by the binary mask of the tissue under test and the collection correction image to generate a background fluorescence image.

5. The bone infection image acquisition method based on bacterial autofluorescence according to claim 1, characterized in that, The step of generating a total fluorescence image based on the binary mask of the tissue to be tested and the collection calibration map includes: The fluorescence image corresponding to the second wavelength is multiplied by the binary mask of the tissue under test and the collection correction image to generate the total fluorescence image.

6. The bone infection image acquisition method based on bacterial autofluorescence according to claim 1, characterized in that, The method further includes: orthogonally configuring the control polarization module and the detection polarization module.

7. A bone infection image acquisition system based on bacterial autofluorescence, characterized in that, The system executes the bone infection image acquisition method based on bacterial autofluorescence as described in claims 1-6, including: The light source module integrates three LEDs for time-division multiplexing of white light, fluorescence of a first wavelength, and fluorescence of a second wavelength; The light field modulation module is used to generate uniform illumination light fields or sinusoidal / Gray code structured light; The projection lens, located at the rear end of the light field modulation module, is used to project the modulated light field onto the surface of the tissue to be tested. A filter switching device for switching between narrowband fluorescent filters and full-transmission filters; An imaging lens is used to focus the light signal from the tissue being tested. The image acquisition module is used to acquire white light images, fluorescence images corresponding to the first wavelength of fluorescence, and fluorescence images corresponding to the second wavelength of fluorescence in a time-division manner. Drive control module: used to drive and control the light source module, the light field modulation module and the filter switching device to realize light source switching, structured light projection and filter switching; The data analysis and processing module is used to process the white light image, the fluorescence image corresponding to the first wavelength of fluorescence, and the fluorescence image corresponding to the second wavelength of fluorescence acquired by the image acquisition module.

8. The bone infection image acquisition system based on bacterial autofluorescence according to claim 7, characterized in that, Also includes: A polarization module, located at the rear end of the projection lens, is used to generate linearly polarized excitation light; The polarization detection module is located at the front end of the imaging lens, and its polarization direction is orthogonal to the polarization induction module.

9. The bone infection image acquisition system based on bacterial autofluorescence according to claim 7, characterized in that, The light field modulation module employs a digital micromirror device or a liquid crystal spatial light modulator.

10. The bone infection image acquisition system based on bacterial autofluorescence according to claim 7, characterized in that, The image acquisition module includes a CCD sensor, a CMOS sensor, or an sCMOS sensor.

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