Detection And Evaluation Method Of Ultrasonic Easy Developing Mesh Based On Time Change

Abdominal wall incisional hernia refers to a type of abdominal disease in which the patient,after undergoing abdominal surgery,presents with progressive protrusion of the abdominal viscera through the surgical incision area toward the body surface due to poor healing of the tendon membrane layer.Surgical intervention is the effective and only way to cure incisional hernias,and the surgical procedure is mainly to implant a mesh at the abdominal wall defect to reposition the protrusion.Among the various hernia mesh types currently on the market,light-weight type meshes have shown significant advantages,both in terms of their physical properties and in the area of chronic pain in patients.Therefore,light-weight meshes are the main research object,but none of the current three medical imaging modalities can image light-weight meshes significantly and effectively.Automated three-dimensional breast ultrasound(ABUS),as a relatively well-established three-dimensional ultrasound equipment,has not only been successfully used on breast examination,but also widely used in the diagnosis of abdominal wall hernias.The characteristics of the ABUS device can only cleverly solve the problems above light-weight mesh cannot effectively and significantly image,but the massive data presented by its device also brings some new problems to the subsequent processing of image analysis.In view of the existing technical problems with ABUS devices and light-weight meshes,the analysis will be conducted from the following two aspects: first,for the ABUS devices themselves,because the size of the device probe directly affects the imaging field of view,an automatic conjunctive method for the ABUS breast ultrasound panorama is proposed,which has been experimentally confirmed,and the breast ultrasound panorama is able to allow physicians to screen breast cancer cases more precisely and objectively.The technique itself is an expansion of the field of view of the device,so it can likewise be applied to ABUS ultrasound images of light-weight type hernia meshes.Second,judging from the nature of the light-weight mesh itself,at the time of hernia repair ultrasonography,the resolution of ultrasound images decreased gradually as the depth of imaging increased.Especially for patients with abdominal wall hernias with thick fat layer,the differences between in vivo implanted meshes and adjacent abdominal tissues are difficult to differentiate by the mesh texture characteristics of light-weight type meshes.In response to this problem,this paper proposes a preparation method for ultrasonically tractable meshes based on the ultrasonic imaging mechanism innovatively,and its effectiveness is verified experimentally.Because ABUS ultrasound images undergo manual proofreading that is timeconsuming and can easily miss the diagnosis of tiny or abnormal areas,in this paper,we propose an algorithm for the automatic detection of abdominal wall incisional hernia meshes based on three-dimensional convolutional neural networks,and the accuracy of the algorithm was verified both ex vivo and in vivo 94.2%,which achieves a noninvasive localization based diagnostic analysis for the postoperative situation after implantation of mesh.At present,there is still a lack of research on the quantification of postoperative morphological characteristics of lightweight patch and the probability prediction of postoperative hernia recurrence.In order to solve the above problems,after further analysis and experiment,this paper proposes a morphological analysis method of lightweight patch based on time change after hernia repair.This method can quantitatively characterize the morphology of lightweight patch in patients after hernia repair.According to the experimental data,it can be found that the average shrinkage rate of patch is 20.2%(7.1%),and the shrinkage range is 9.7% ～ 29.4%,These data can effectively help reduce or even avoid the probability of postoperative hernia recurrence and other complications.