Personalized 3D printing mask based on MRI reconstruction and preparation method thereof

Abstract

The invention discloses a personalized 3D printing mask based on MRI (Magnetic Resonance Imaging) reconstruction and a preparation method thereof. The method comprises the following steps: scanning a human face by using magnetic resonance equipment to obtain human face MRI data, and generating a human face three-dimensional model according to the human face MRI data; taking the human face three-dimensional model as a reference to generate a three-dimensional mold which is completely fitted with the face contour; extracting physiological parameters of the human face skin from the human face MRI data by adopting a medical image platform, and performing quantitative analysis on the physiological state of the human face skin according to the physiological parameters to obtain a quantitative analysis result; and adopting biological 3D printing equipment, taking a three-dimensional mold as a carrier, and combining the quantitative analysis result to carry out 3D printing, so as to obtain the 3D printing mask. The 3D printing facial mask prepared by the method can be highly fit with the facial contour of a human body, and skin problems of different facial areas can be accurately nursed.

Description

Technical Field

[0001] The present invention relates to the technical field of beauty and skin care, and in particular to a personalized 3D printed facial mask based on MRI reconstruction and a preparation method thereof. Background Art

[0002] With the continuous improvement of socioeconomic levels and quality of life, consumer demand for beauty and skincare has rapidly evolved from basic care to personalized, precision-focused treatments. As a crucial vehicle for daily skincare, facial masks' form, adaptability, and targeted functionality directly impact the user experience and effectiveness of their treatments.

[0003] Traditional facial masks are mostly designed based on standardized facial models, using flat cutting or uniform non-woven fabrics. They are difficult to adapt to the different characteristics of individual facial bone structure, muscle distribution, and skin curvature. When applied, they are prone to partial hanging, wrinkling, or edge lifting, resulting in uneven penetration of active ingredients. They may even cause shedding or residual bubbles due to insufficient fit, seriously affecting skin care results. In recent years, 3D printed facial masks based on optical 3D scanning have emerged. Compared with traditional facial masks, they have a higher fit, but they still have the following defects:

[0004] (1) The optical imaging technology that existing 3D printed masks rely on can only obtain skin surface contour information. Optical scanning is easily affected by ambient light intensity, angle, and reflectivity, resulting in loss of surface details or geometric deformation of the collected model (such as distortion of data in the nasal grooves and eye sockets). Such errors are further amplified during the mold generation process. There is still a gap between the final prepared mask and the actual facial contour, making it difficult to achieve true "zero fit", which affects the penetration efficiency of active ingredients and user experience.

[0005] (2) Existing 3D printed masks are based on two-dimensional curved surfaces with uniform layer thickness. They lack adaptive support structures for complex curved surfaces such as zygomatic protrusions and mandibular angles. Such planar designs are prone to local tension concentration due to uneven mechanical distribution during application, causing the membrane to warp or compress sensitive areas (such as the eye area), which not only reduces wearing comfort but also may increase the risk of skin barrier damage.

[0006] (3) Existing 3D printed facial masks mostly use a “same formula for the whole face” and cannot provide precise care for skin problems in different facial areas. Summary of the Invention

[0007] In order to solve the above technical problems, the present invention provides a personalized 3D printed facial mask based on MRI reconstruction and a preparation method thereof. The prepared 3D printed facial mask can be highly fitted with the human facial contour and provide precise care for skin problems in different facial areas.

[0008] In order to solve the above problems, the present invention adopts the following technical solutions:

[0009] The present invention provides a method for preparing a personalized 3D printed facial mask based on MRI reconstruction, comprising the following steps:

[0010] S1: Scanning a human face using a magnetic resonance imaging device to obtain MRI data of the human face, and generating a three-dimensional model of the human face based on the MRI data of the human face;

[0011] S2: Based on the 3D model of the human face, a 3D mold is generated that fits the facial contour perfectly.

[0012] S3: Using a medical imaging platform to extract physiological parameters of human facial skin from human facial MRI data, quantitatively analyze the physiological state of human facial skin based on the physiological parameters to obtain quantitative analysis results;

[0013] S4: Using biological 3D printing equipment, using a three-dimensional mold as a carrier, combined with the quantitative analysis results, 3D printing is performed to obtain a 3D printed mask.

[0014] Preferably, step S1 includes the following steps:

[0015] S11: Using a magnetic resonance imaging device to perform T1-weighted imaging scan, proton density-weighted imaging scan, diffusion-weighted imaging scan, and blood oxygen level-dependent imaging scan on the human face to obtain human facial MRI data;

[0016] S12: Multi-planar reconstruction and 3D segmentation of facial MRI data are performed on the medical imaging platform to accurately extract information about the facial skin surface, subcutaneous tissue, and facial bone contours, generating a 1:1 3D model of the human face containing anatomical details.

[0017] Preferably, the specific steps of step S2 are as follows: in the three-dimensional modeling software, taking the three-dimensional model of the human face as a reference, expanding the preset distance in the normal direction of the facial skin surface through a pixel-level expansion algorithm, and using a surface adaptive algorithm to optimize the curvature of the nose and eye socket areas to ensure continuity and smoothness, and generate a three-dimensional mold that fits the facial contour perfectly.

[0018] Preferably, the specific steps of step S3 are as follows: using a medical imaging platform to extract physiological parameters of human facial skin from human facial MRI data, the physiological parameters including sebum secretion distribution, inflammation distribution, skin moisture distribution, erythema distribution, and fat thickness distribution, and performing quantitative analysis on the physiological state of human facial skin according to the physiological parameters to obtain quantitative analysis results, the quantitative analysis results including a sebum heat map, inflammation distribution map, skin moisture gradient map, erythema index map, and barrier function index map of the human face.

[0019] Preferably, step S4 includes the following steps:

[0020] S41: dividing the human face into a high curvature area, a low curvature area, and a transition area according to skin curvature based on the human face three-dimensional model, wherein the transition area is located between the high curvature area and the low curvature area, and dividing each area into a plurality of functional areas based on the quantitative analysis results;

[0021] S42: determining the functional component groups in the facial mask solution according to the functional zones, and determining the cross-linking agent concentration in the facial mask solution according to the areas where the functional zones are located, thereby obtaining a facial mask solution corresponding to each functional zone;

[0022] S43: Using a biological 3D printing device and a three-dimensional mold as a carrier, 3D printing is performed on each functional area using a corresponding mask solution to obtain a 3D printed mask.

[0023] Preferably, the plurality of functional zones include one or more of a dry and dehydrated area, an oily area, a sensitive and red area, an aging wrinkle area, a pigmentation area, and an enlarged pore area.

[0024] Preferably, the facial mask solution comprises a facial mask base liquid and a functional component group, wherein the facial mask base liquid comprises water, a film former, a plasticizer, a cross-linking agent, a surfactant, and a moisturizer;

[0025] The functional component group corresponding to the dry and water-deficient area includes hyaluronic acid, ceramide, and squalane;

[0026] The functional ingredient group corresponding to the oil-rich area includes salicylic acid, tea tree essential oil, and niacinamide;

[0027] The functional ingredient group corresponding to the sensitive redness area includes asiaticoside, panthenol, and bisabolol;

[0028] The functional ingredient group corresponding to the aging wrinkle area includes retinol, polypeptide, and bosera;

[0029] The functional ingredient group corresponding to the pigmentation area includes vitamin C derivatives, arbutin, and niacinamide;

[0030] The functional ingredient group corresponding to the enlarged pore area includes gluconolactone, bakuchiol, and witch hazel extract.

[0031] Preferably, the method for determining the cross-linking agent concentration in the mask solution according to the area where the functional partition is located in step S42 is as follows:

[0032] If the functional partition is located in a high curvature area, the cross-linker concentration in the mask solution is a; if the functional partition is located in a low curvature area, the cross-linker concentration in the mask solution is b; if the functional partition is located in a transition area, the cross-linker concentration in the mask solution is c, a>c>b.

[0033] Preferably, when the biological 3D printing equipment in step S43 uses the corresponding mask solution to perform 3D printing on each functional partition, if the functional partition is located in the high curvature area, the printing thickness of the functional partition is d; if the functional partition is located in the low curvature area, the printing thickness of the functional partition is f; if the functional partition is located in the transition area, the printing thickness of the functional partition gradually decreases from the side close to the high curvature area to the side close to the low curvature area, the printing thickness close to the high curvature area is d, and the printing thickness close to the low curvature area is f, d>f.

[0034] The present invention provides a 3D printed facial mask prepared by the above method.

[0035] The beneficial effects of the present invention are: (1) The three-dimensional model constructed based on the user's individual human facial MRI data can accurately restore the millimeter-level anatomical details of the facial bones, muscles and skin tissues (such as the depth of the nasal wing grooves and the radius of the zygomatic bone curvature), and combine with the pixel expansion algorithm to generate a three-dimensional mold to ensure zero-gap fit between the mask and the facial contour. (2) The user's face is divided into regions according to the skin curvature. The mask printing thickness and cross-linking agent concentration are increased in the high curvature region to increase the elastic modulus, which is significantly higher than that in the low curvature region (i.e., the flat region), thereby effectively resisting the deformation caused by facial micro-expressions and avoiding warping or breakage of the membrane; the mask printing thickness and cross-linking agent concentration are reduced in the low curvature region to make the mechanical properties of the membrane adapt to the natural ductility of the skin, ensuring wearing comfort and breathability; in the transition region, the mask printing thickness is gradually reduced from the side close to the high curvature region to the side close to the low curvature region, with a linear gradient, and the cross-linking agent concentration is between the cross-linking agent concentrations in the high curvature region and the low curvature region, eliminating the sudden change in mechanical properties, and achieving "rigid and flexible" mechanical adaptation in complex anatomical regions (such as the nasal wing groove and the mandibular line). By dynamically regulating the layer thickness and cross-linking agent concentration gradient, the mechanical properties of the mask (such as elastic modulus and anti-deformation ability) are accurately matched with the facial contour. (3) The physiological parameters of the human facial skin are extracted from the user's individual facial MRI data and quantitatively analyzed. Each area is divided into several functional zones according to the quantitative analysis results, and a mask solution with a corresponding functional ingredient group is printed for each functional zone, so that the skin problems of each functional zone can be accurately cared for. BRIEF DESCRIPTION OF THE DRAWINGS

[0036] Figure 1 is a flow chart of an embodiment. DETAILED DESCRIPTION

[0037] The technical solution of the present invention will be further specifically described below through embodiments and in conjunction with the accompanying drawings.

[0038] Example 1: This example is a method for preparing a personalized 3D printed mask based on MRI reconstruction, such as Figure 1 As shown, the following steps are included:

[0039] S1: Scan the human face using a magnetic resonance imaging device to obtain MRI data of the human face, and generate a three-dimensional model of the human face based on the MRI data of the human face;

[0040] S2: Based on the 3D model of the human face, a 3D mold is generated that fits the facial contour perfectly.

[0041] S3: Using a medical imaging platform to extract physiological parameters of human facial skin from human facial MRI data, quantitatively analyze the physiological state of human facial skin based on the physiological parameters to obtain quantitative analysis results;

[0042] S4: Using biological 3D printing equipment, using a three-dimensional mold as a carrier, combined with the quantitative analysis results, 3D printing is performed to obtain a 3D printed mask.

[0043] Step S1 includes the following steps:

[0044] S11: Using a magnetic resonance imaging device to perform T1-weighted imaging scan, proton density-weighted imaging scan, diffusion-weighted imaging scan, and blood oxygen level-dependent imaging scan on the human face to obtain human facial MRI data;

[0045] S12: Through the medical imaging platform (Mimics), multi-planar reconstruction and three-dimensional segmentation of human facial MRI data are performed to accurately extract the facial skin surface, facial subcutaneous tissue, and facial bone contour information, and generate a 1:1 human facial three-dimensional model containing anatomical details (such as nasal wing grooves, zygomatic bone curvature, and jawline direction).

[0046] The medical imaging platform Mimics is continuously optimized through grayscale threshold segmentation, edge detection algorithms, and manual layer-by-layer correction to ensure millimeter-level geometric accuracy.

[0047] The specific steps of step S2 are as follows: in the three-dimensional modeling software, using the three-dimensional model of the human face as a reference, expand the preset distance (0.5 to 1.0 mm) in the normal direction of the facial skin surface through a pixel-level expansion algorithm, and use a surface adaptive algorithm to optimize the curvature of the nose and eye socket areas to ensure continuity and smoothness, and generate a three-dimensional mold in STL format that fully fits the facial contour.

[0048] The three-dimensional mold is optimized through a surface adaptive algorithm to ensure the continuous smoothness of complex areas such as the nose wings and eye sockets, avoiding the fitting failure of traditional flat molds caused by sudden changes in curvature.

[0049] The specific steps of step S3 are as follows: using a medical imaging platform to extract physiological parameters of human facial skin from human facial MRI data, the physiological parameters including sebum secretion distribution, inflammation distribution, skin moisture distribution, erythema distribution, and fat thickness distribution, and performing quantitative analysis on the physiological state of human facial skin based on the physiological parameters to obtain quantitative analysis results, which include a sebum heat map, inflammation distribution map, skin moisture gradient map, erythema index map, and barrier function index map of the human face.

[0050] T1-weighted imaging scan data can assess sebum secretion and inflammation, proton density-weighted imaging scan data can assess skin moisture and fat thickness, diffusion-weighted imaging scan data can assess transepidermal water loss rate, and blood oxygen level-dependent imaging scan data can assess erythema index.

[0051] Step S4 includes the following steps:

[0052] S41: dividing the human face into a high curvature area, a low curvature area, and a transition area according to skin curvature based on the human face three-dimensional model, wherein the transition area is located between the high curvature area and the low curvature area, and dividing each area into a plurality of functional areas based on the quantitative analysis results;

[0053] Several functional zones include one or more of the following: dry and dehydrated zone, oily zone, sensitive and red zone, aging wrinkle zone, pigmentation zone, and enlarged pore zone;

[0054] S42: determining the functional component groups in the facial mask solution according to the functional zones, and determining the cross-linking agent concentration in the facial mask solution according to the areas where the functional zones are located, thereby obtaining a facial mask solution corresponding to each functional zone;

[0055] The facial mask solution includes a facial mask base liquid and a functional component group, wherein the facial mask base liquid includes water, a film former, a plasticizer, a cross-linking agent, a surfactant, and a moisturizer;

[0056] The functional ingredient group corresponding to the dry and dehydrated area includes hyaluronic acid, ceramide, and squalane, which are used to deeply replenish water, repair the barrier, and lock in moisture;

[0057] The functional ingredient group corresponding to the oil-rich area includes salicylic acid, tea tree oil, and niacinamide, which are used to control oil and inflammation, unclog pores, and regulate sebum;

[0058] The functional ingredient group corresponding to the sensitive redness area includes Centella asiatica, Panthenol, and Bisabolol, which are used to soothe inflammation, repair the barrier, and reduce sensitivity;

[0059] The functional ingredient group corresponding to the aging wrinkle area includes retinol, peptides, and phosphatase, which are used to promote collagen regeneration, reduce fine lines, and improve firmness;

[0060] The functional ingredient group corresponding to the pigmentation area includes vitamin C derivatives, arbutin, and niacinamide, which are used to inhibit tyrosinase, block melanin transport, and brighten the skin tone;

[0061] The functional ingredient group corresponding to the enlarged pores area includes gluconolactone, bakuchiol, and witch hazel extract, which are used for gentle exfoliation, pore tightening, and anti-oxidation;

[0062] The method for determining the crosslinker concentration in the mask solution according to the area where the functional partition is located is as follows:

[0063] If the functional partition is located in a high curvature area, the cross-linking agent concentration in the mask solution is a; if the functional partition is located in a low curvature area, the cross-linking agent concentration in the mask solution is b; if the functional partition is located in a transition area, the cross-linking agent concentration in the mask solution is c, a>c>b;

[0064] S43: Using a biological 3D printing device and a three-dimensional mold as a carrier, 3D printing is performed on each functional area using a corresponding mask solution to obtain a 3D printed mask;

[0065] When the biological 3D printing equipment uses the corresponding mask solution to perform 3D printing on each functional partition, if the functional partition is located in the high curvature area, the printing thickness of the functional partition is d; if the functional partition is located in the low curvature area, the printing thickness of the functional partition is f; if the functional partition is located in the transition area, the printing thickness of the functional partition gradually decreases from the side close to the high curvature area to the side close to the low curvature area (for example, linearly decreases), the printing thickness close to the high curvature area is d, and the printing thickness close to the low curvature area is f, d>f.

[0066] In this scheme, first, the user's individual facial MRI data is obtained, and the human facial MRI data is reconstructed and three-dimensionally segmented through a medical imaging platform to generate a 1:1 human facial three-dimensional model containing anatomical details (accuracy ±0.1mm). Then, based on the three-dimensional model, it is expanded outward by 0.8mm along the normal direction, and a surface adaptive algorithm is used to optimize the curvature of the nose and eye socket areas to ensure continuity and smoothness, and a three-dimensional mold in STL format that completely fits the facial contour is generated. Then, the medical imaging platform is used to extract the physiological parameters of the human facial skin from the human facial MRI data and perform quantitative analysis. Finally, a regional skin problem atlas with anatomical positioning accuracy and physiological parameter annotations is generated, and a multi-nozzle biological 3D printer is used for functional zoning printing to obtain a 3D printed facial mask.

[0067] The three-dimensional model constructed based on the user's individual facial MRI data can accurately restore the millimeter-level anatomical details of the facial bones, muscles and skin tissues (such as the depth of the nasal wing grooves and the radius of the zygomatic bone curvature), and combine with the pixel expansion algorithm to generate a three-dimensional mold to ensure zero gap fit between the mask and the facial contour.

[0068] The user's individual face is divided into regions according to skin curvature. The mask printing thickness and cross-linker concentration are increased in high-curvature areas (such as the zygomatic protuberance and nasolabial folds), increasing the elastic modulus to be significantly higher than that in low-curvature areas (i.e., flat areas such as the cheeks and forehead), thereby effectively resisting deformation caused by facial micro-expressions and avoiding warping or breakage of the membrane. The mask printing thickness and cross-linker concentration are reduced in low-curvature areas to adapt the membrane's mechanical properties to the natural ductility of the skin, ensuring wearing comfort and breathability. In transition areas (such as the junction of the zygomatic bone and cheek), the mask printing thickness is gradually reduced from the side close to the high-curvature area to the side close to the low-curvature area, with a linear gradient. The cross-linker concentration is located between the cross-linker concentrations in the high-curvature and low-curvature areas, eliminating sudden changes in mechanical properties. In complex anatomical areas (such as the nasal sulcus and jawline), "rigid and flexible" mechanical adaptation is achieved. By dynamically adjusting the layer thickness and cross-linker concentration gradient, the mechanical properties of the mask (such as elastic modulus and deformation resistance) are precisely matched to the facial contour.

[0069] The physiological parameters of human facial skin are extracted from the user's individual facial MRI data and quantitatively analyzed. Based on the quantitative analysis results, each area is divided into several functional zones, and a mask solution with a corresponding functional ingredient group is printed for each functional zone, so that precise care can be provided for skin problems in each functional zone.

[0070] Test results show that the 3D printed mask fits well with the face, and the average gap is significantly smaller than that of existing masks, especially the maximum gap at the nose wings is significantly reduced, and the tensile strength is significantly improved. It accurately releases corresponding functional ingredient groups for different problems of the user's facial skin, achieving precise care, thereby improving the skin care effect of the mask.

[0071] This embodiment provides a 3D printed facial mask prepared as described above.

[0072] Example 2: This example is a method for preparing a personalized 3D printed facial mask based on MRI reconstruction. Only step S4 is different from that of Example 1, and the other steps are the same.

[0073] Step S4 includes the following steps:

[0074] S41: Divide the human face into several functional areas according to the quantitative analysis results;

[0075] S42: determining functional component groups in the facial mask solution according to the functional zones, thereby obtaining facial mask solutions corresponding to each functional zone;

[0076] S43: Using a biological 3D printing device and a three-dimensional mold as a carrier, 3D printing is performed on each functional area using a corresponding mask solution to obtain a 3D printed mask.

[0077] Several functional zones include one or more of dry and dehydrated areas, oily areas, sensitive and red areas, aging wrinkle areas, pigmentation areas, and large pore areas.

[0078] The facial mask solution includes a facial mask base liquid and a functional component group, wherein the facial mask base liquid includes water, a film former, a plasticizer, a cross-linking agent, a surfactant, and a moisturizer;

[0079] The functional ingredient group corresponding to the dry and dehydrated area includes hyaluronic acid, ceramide, and squalane, which are used to deeply replenish water, repair the barrier, and lock in moisture;

[0080] The functional ingredient group corresponding to the oil-rich area includes salicylic acid, tea tree oil, and niacinamide, which are used to control oil and inflammation, unclog pores, and regulate sebum;

[0081] The functional ingredient group corresponding to the sensitive redness area includes Centella asiatica, Panthenol, and Bisabolol, which are used to soothe inflammation, repair the barrier, and reduce sensitivity;

[0082] The functional ingredient group corresponding to the aging wrinkle area includes retinol, peptides, and phosphatase, which are used to promote collagen regeneration, reduce fine lines, and improve firmness;

[0083] The functional ingredient group corresponding to the pigmentation area includes vitamin C derivatives, arbutin, and niacinamide, which are used to inhibit tyrosinase, block melanin transport, and brighten the skin tone;

[0084] The functional ingredient group corresponding to the enlarged pore area includes gluconolactone, bakuchiol, and witch hazel extract, which are used for gentle exfoliation, tightening pores, and anti-oxidation.

[0085] This embodiment provides a 3D printed facial mask prepared as described above.

Claims

1. A method for preparing a personalized 3D printed facial mask based on MRI reconstruction, characterized in that: The following steps are involved: S1: Scan the human face using a magnetic resonance imaging device to obtain MRI data of the human face, and generate a three-dimensional model of the human face based on the MRI data of the human face; S2: Based on the human face 3D model, a 3D mold is generated that fits the facial contour perfectly. S3: Using a medical imaging platform to extract physiological parameters of human facial skin from human facial MRI data, quantitatively analyze the physiological state of human facial skin based on the physiological parameters to obtain quantitative analysis results; S4: Using biological 3D printing equipment, using a three-dimensional mold as a carrier, combined with the quantitative analysis results, 3D printing is performed to obtain a 3D printed mask.

2. The method for preparing a personalized 3D printed facial mask based on MRI reconstruction according to claim 1, characterized in that: The step S1 comprises the following steps: S11: Using a magnetic resonance imaging device to perform T1-weighted imaging scan, proton density-weighted imaging scan, diffusion-weighted imaging scan, and blood oxygen level-dependent imaging scan on the human face to obtain human facial MRI data; S12: Multi-planar reconstruction and 3D segmentation of facial MRI data are performed on the medical imaging platform to accurately extract information about the facial skin surface, subcutaneous tissue, and facial bone contours, generating a 1:1 3D model of the human face containing anatomical details.

3. The method for preparing a personalized 3D printed facial mask based on MRI reconstruction according to claim 1, characterized in that: The specific steps of step S2 are as follows: in the three-dimensional modeling software, using the three-dimensional model of the human face as a reference, a preset distance is expanded in the normal direction of the facial skin surface through a pixel-level expansion algorithm, and a surface adaptive algorithm is used to optimize the curvature of the nose and eye socket areas to ensure continuity and smoothness, thereby generating a three-dimensional mold that completely fits the facial contour.

4. The method for preparing a personalized 3D printed facial mask based on MRI reconstruction according to claim 1, characterized in that: The specific steps of step S3 are as follows: using a medical imaging platform to extract physiological parameters of human facial skin from human facial MRI data, the physiological parameters including sebum secretion distribution, inflammation distribution, skin moisture distribution, erythema distribution, and fat thickness distribution; performing a quantitative analysis on the physiological state of human facial skin based on the physiological parameters to obtain quantitative analysis results, the quantitative analysis results including a sebum heat map, an inflammation distribution map, a skin moisture gradient map, an erythema index map, and a barrier function index map of the human face.

5. The method for preparing a personalized 3D printed facial mask based on MRI reconstruction according to claim 1, characterized in that: The step S4 comprises the following steps: S41: dividing the human face into a high curvature area, a low curvature area, and a transition area according to skin curvature based on the human face three-dimensional model, wherein the transition area is located between the high curvature area and the low curvature area, and dividing each area into a plurality of functional areas based on the quantitative analysis results; S42: determining the functional component groups in the facial mask solution according to the functional zones, and determining the cross-linking agent concentration in the facial mask solution according to the areas where the functional zones are located, thereby obtaining a facial mask solution corresponding to each functional zone; S43: Using a biological 3D printing device and a three-dimensional mold as a carrier, 3D printing is performed on each functional area using a corresponding mask solution to obtain a 3D printed mask.

6. The method for preparing a personalized 3D printed facial mask based on MRI reconstruction according to claim 5, characterized in that: The functional zones include one or more of a dry and dehydrated area, an oily area, a sensitive and red area, an aging wrinkle area, a pigmentation area, and an enlarged pore area.

7. The method for preparing a personalized 3D printed facial mask based on MRI reconstruction according to claim 6, characterized in that: The facial mask solution comprises a facial mask base liquid and a functional component group, wherein the facial mask base liquid comprises water, a film former, a plasticizer, a cross-linking agent, a surfactant, and a moisturizer; The functional component group corresponding to the dry and water-deficient area includes hyaluronic acid, ceramide, and squalane; The functional ingredient group corresponding to the oil-rich area includes salicylic acid, tea tree essential oil, and niacinamide; The functional ingredient group corresponding to the sensitive redness area includes asiaticoside, panthenol, and bisabolol; The functional ingredient group corresponding to the aging wrinkle area includes retinol, peptide, and prostaglandin; the functional ingredient group corresponding to the pigmentation area includes vitamin C derivatives, arbutin, and niacinamide; The functional ingredient group corresponding to the enlarged pore area includes gluconolactone, bakuchiol, and witch hazel extract.

8. The method for preparing a personalized 3D printed facial mask based on MRI reconstruction according to claim 5, characterized in that: The method for determining the cross-linking agent concentration in the mask solution according to the area where the functional partition is located in step S42 is as follows: If the functional partition is located in a high curvature area, the cross-linker concentration in the mask solution is a; if the functional partition is located in a low curvature area, the cross-linker concentration in the mask solution is b; if the functional partition is located in a transition area, the cross-linker concentration in the mask solution is c, a>c>b.

9. The method for preparing a personalized 3D printed facial mask based on MRI reconstruction according to claim 8, characterized in that: When the biological 3D printing device uses the corresponding mask solution to perform 3D printing on each functional partition in step S43, if the functional partition is located in the high curvature area, the printing thickness of the functional partition is d; if the functional partition is located in the low curvature area, the printing thickness of the functional partition is f; if the functional partition is located in the transition area, the printing thickness of the functional partition gradually decreases from the side close to the high curvature area to the side close to the low curvature area, the printing thickness close to the high curvature area is d, and the printing thickness close to the low curvature area is f, d>f.

10. A 3D printed facial mask prepared by the preparation method according to any one of claims 1 to 9.

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