Application of Treatment Simulation Software for War Injury in Emergency Treatment Training on the Battlefield based on Chinese Visible Human Datasets

Background: Proficiency in self-help and mutual aid skills is correlated with the prognosis of injured patients, and this study aims to create treatment simulation software for war injuries that reflect the physical constitution of Chinese people and study its application in first aid training on the battlefield. Methods: Based on thin-sectional, highly precise Chinese Visible Human (CVH) data with high resolution, combined with self-help and mutual medical aid measures such as digital pressure hemostasis, cricothyroid membrane puncture, pneumothorax puncture and bone marrow puncture for battlefield first aid, useing Amira and other softwares to building the simulation software for the technical training of military medical students and basic medical officers was constructed. Eighty medical service students were trained on battlefield first aid technology, and a new training mode for the treatment of war injuries was developed and optimized. Results: Simulation software of hemostasis and puncture for battlefield first aid that was suitable for the technical training of military medical students and its supporting teaching materials 3D-PDF were established. The software included modules of hemostasis of the vertex, face, head-shoulder, shoulder-arm, forearm, upper forearm, lower limb and foot and puncture of the cricothyroid membrane , pneumothorax, and bone marrow cavity. Collaborating with interactive 3D-PDF, it was successfully used for on-site first aid training of military medical students. The questionnaire results showed that the trainees had a high recognition of the human-computer interactive performance of the software with a clear interface and easy operation. The accuracy and richness of the three-dimensional model structure, knowledge of hemostasis and puncture and applied anatomy contained in this software were high, helping trainees to quickly master the knowledge points and operation techniques related to hemostasis and puncture. Conclusion: The system can effectively mobilize the learning enthusiasm of students and fully improve the learning efficiency of the basic materials and applied anatomy of battlefield first aid, as well as the teaching efficiency of teachers. The training simulation of battlefield first aid, comprising a combination of various modes, effectively complemented each other, met many training needs, and achieved satisfactory training results. Additionally, this software could be used in the emergency training of traffic accident injuries and disaster-related injuries.

Construction of a registration and fusion of unreformed thin-sectional high-resolution sectional anatomical image (Chinese Visible Human images) and CT and MRI images based on B-spline and mutual information and its application in segmenting nasopharyngeal structures in Treatment Planning System (TPS)

Background To help radiotherapy doctors recognize and segment the nasopharyngeal organs in risk of Nasopharyngeal carcinoma (NPC) and make radiotherapy plan. Materials/Methods: Based on the continuous thin-layer, high-precision, high-resolution and true-color sectional anatomical data (Chinese Visible Human (CVH) images),we used B-spline and mutual information to transform, register and fuse the CVH images with the patient's personalized CT images, and integrated them into the Treatment Planning System (TPS). Consequently, Three-Dimensional Visualization Treatment Planning System (3DV + TPS) was created. To verify it, 3DV + TPS was deployed to identify and segment the nasopharyngeal organs in risk of NPC, and a questionnaire was filled out by radiotherapy doctors. Results Result shows that 3DV + TPS can finish registration and fusion of 4 sets of sectional anatomical images and individual CT images of patients in approximately 3 minutes and 50 seconds. Conclusion The registered and fused images can accurately reflect the position, outline and adjacent space of the nasopharyngeal structure which is not clear in the CT images. Thus, it is helpful for recognizing and segmenting neural, muscular and glandular structures. Through automatically registering and fusing of color images and CT gray images, 3DV + TPS improves the accuracy and efficiency of recognizing nasopharyngeal structures in making radiotherapy plan, and it is useful to improve the teaching quality of tumor radiotherapy for medical students and interns as well.

Segmenting Brain Tissues from Chinese Visible Human Dataset by Deep-Learned Features with Stacked Autoencoder

Cryosection brain images in Chinese Visible Human (CVH) dataset contain rich anatomical structure information of tissues because of its high resolution (e.g., 0.167 mm per pixel). Fast and accurate segmentation of these images into white matter, gray matter, and cerebrospinal fluid plays a critical role in analyzing and measuring the anatomical structures of human brain. However, most existing automated segmentation methods are designed for computed tomography or magnetic resonance imaging data, and they may not be applicable for cryosection images due to the imaging difference. In this paper, we propose a supervised learning-based CVH brain tissues segmentation method that uses stacked autoencoder (SAE) to automatically learn the deep feature representations. Specifically, our model includes two successive parts where two three-layer SAEs take image patches as input to learn the complex anatomical feature representation, and then these features are sent to Softmax classifier for inferring the labels. Experimental results validated the effectiveness of our method and showed that it outperformed four other classical brain tissue detection strategies. Furthermore, we reconstructed three-dimensional surfaces of these tissues, which show their potential in exploring the high-resolution anatomical structures of human brain.

Compute Three-Dimensional Reconstruction of Brachial Plexus and its Surrounding Tissues by Using Chinese Visible Human (CVH) Data Anatomical Foundation for Brachial Plexus Entrapment

We selected cervical cross section image from CVH-F1 (Chinese Visible Human Female, No.1) database. After labeling the relative structures, we made 3D reconstruction of brachial plexus and surrounding tissue by computer reconstruction technique. In cervical cross section image, tissues like vertebrae, disc, spinal dura mater, spinal cord, vertebral artery, nerve root and muscles can be recognized, which ensure the ideal effect of 3-D reconstruction. In conclusion, we can make 3-D reconstruction of brachial plexus through computer technique which may serve for anatomical study of brachial plexus compression. After that we made vertical section on the nerve and calculate the ratio between area of nerve and its gap. In result, it is suggested that the nerve passage for root and strand is comparatively narrower.