A Web Simulation of Medical Image Reconstruction and Processing as an Educational Tool

Abstract

Web educational resources integrating interactive simulation tools provide students with an in-depth understanding of the medical imaging process. The aim of this work was the development of a purely Web-based, open access, interactive application, as an ancillary learning tool in graduate and postgraduate medical imaging education, including a systematic evaluation of learning effectiveness. The pedagogic content of the educational Web portal was designed to cover the basic concepts of medical imaging reconstruction and processing, through the use of active learning and motivation, including learning simulations that closely resemble actual tomographic imaging systems. The user can implement image reconstruction and processing algorithms under a single user interface and manipulate various factors to understand the impact on image appearance. A questionnaire for pre-and post-training self-assessment was developed and integrated in the online application. The developed Web-based educational application introduces the trainee in the basic concepts of imaging through textual and graphical information and proceeds with a learning-by-doing approach. Trainees are encouraged to participate in a pre-and post-training questionnaire to assess their knowledge gain. An initial feedback from a group of graduate medical students showed that the developed course was considered as effective and well structured. An e-learning application on medical imaging integrating interactive simulation tools was developed and assessed in our institution.

A comparison of student performance and satisfaction between a traditional and integrative approach to teaching an introductory radiology course on the extremities

“…As mentioned previously, e-learning can be a very effective tool when used in conjunction with a user-friendly LMS. [8][9][10][11] Although workload was perceived as being greater during the first 2 trimesters of the transition to the integrative approach, there was no difference between the educational delivery methods in the content or the volume of materials presented. During the transition to the integrative approach, students may have perceived a greater workload as they were still adapting to the best way to utilize the computer-aided learning tools.…”

“…During the ongoing curriculum review from September 2009 to August 2011, the instructor of the extremities radiology course began to explore e-learning since previous studies concluded that e-learning was an effective educational tool when used in conjunction with a user-friendly LMS. [8][9][10][11] Key findings during this exploration phase that resonated with the instructor were that (1) students perceived that the computer-assisted model provided better quality of instruction than did the traditional view box teaching format; 5 (2) students became less engaged in their learning environment when crowded around view boxes, 5 and (3) blended-learning approaches improved prelaboratory preparation and facilitated student learning. [1][2][3][4][5][6][7] Simultaneously with the instructor's exploration of e-learning, the institution began to offer online programs that provided the instructor and students with access to a user-friendly LMS.…”

Medicine Students’ Opinions Post-COVID-19 Regarding Online Learning in Association with Their Preferences as Internet Consumers

“…Examples can be given in various medical fields, such as radiology, physiotherapy, nursing, and so on. Medical imagistic teaching can be improved by webbased simulation platforms used to manipulate and process radiological images with reconstruction algorithms, allowing one to fully customize their parameters [8,46]. In physiotherapy, video conference-based telehealth allows to deliver exercise-based interventions (i.e., management of knee osteoarthritis) [42]; the literature reported an increased trend of using online education in this specialty, and 56.3% of the respondents already use e-communication to schedule in-person consultations with patients requiring physiotherapy [47].…”

X-ray image global enhancement algorithm in medical image classification

“…Due to the particularity of medical X-ray image, the image processing should avoid noise introduction, lose details of the image, and image detail distortion [3,9]. The current medical X-ray image global enhancement algorithm has a poor denoising effect, the enhancement effect is not obvious, and the reduction degree of the enhanced image is low [14]. To address the above problem, a global enhancement algorithm for X-ray image in medical image classification is proposed in this paper.…”