Institute of Fundamental Technological Research
Polish Academy of Sciences

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Julianna Dąbrowa


Recent publications
1.  Kolecki R., Pręgowska A., Dąbrowa J., Skuciński J., Pulanecki T., Walecki P., van Dam P.M., Dudek D., Richter P., Proniewska K., Assessment of the utility of mixed reality in medical education, Translational Research in Anatomy, ISSN: 2214-854X, DOI: 10.1016/j.tria.2022.100214, Vol.28, pp.100214-1-6, 2022

Abstract:
Background: Immersive technologies like Mixed Reality (MR), Virtual Reality (VR) and Augmented Reality (AR) are becoming increasingly popular and gain user trust across various fields, particularly in medicine. In this paper we will use the general term Mixed Reality (MR) to refer to the various virtual reality methods, namely VR and AR. These new immersive technologies require varying degrees of instruction, both in their practice use, as well as in how to adjust to interacting with 3D virtual spaces. This study assesses the pedagogical value of these immersive technologies in medical education. Method: We surveyed a group of 211 students and 47 academic faculty at a medical college regarding potential applications of MR in the medical curriculum by using a questionnaire comprised of eight questions. Results were analyzed accounting for user age and professional position, i.e., student vs faculty. Results: 70% of students and 60% of the academic faculty think that MR-supplemented education is advantageous over a classical instruction. Most highly valued were the 3D visualization capabilities of MR, especially in anatomy classes. There was no significant statistical difference between students and faculty responders. Moreover, screensharing between faculty and students contributed to better, longer lasting absorption of knowledge. Surprisingly, the main issue was related to availability, i.e., only 5% of students had access to MR, while 17% of faculty use MR regularly, and 36% occasionally. Conclusions: MR technology can be a valuable resource that supports traditional medical education, especially via 3D anatomy classes, however MR availability needs to be increased. Moreover, MR expands the capabilities and effectiveness of remote learning, which was normalized during the COVID-19 pandemic, to ensure effective student and patient education. MR-based lessons, or even select modules, provide a unique opportunity to ex-change experiences inside and outside the medical community.

Keywords:
mixed reality, e-learning, remote learning, real-time rendering, 3D visualization, medical education

Affiliations:
Kolecki R. - other affiliation
Pręgowska A. - IPPT PAN
Dąbrowa J. - other affiliation
Skuciński J. - Jagiellonian University (PL)
Pulanecki T. - Jagiellonian University (PL)
Walecki P. - other affiliation
van Dam P.M. - PEACS BV, Nieuwerbrug (NL)
Dudek D. - Jagiellonian University (PL)
Richter P. - Jagiellonian University (PL)
Proniewska K. - Jagiellonian University (PL)

Conference papers
1.  Proniewska K., Kolecki R., Grochowska A., Popiela T., Rogula T., Malinowski K., Dołęga-Dołęgowski D., Kenig J., Richter P., Dąbrowa J., Mortada M.J., van Dam P., Pręgowska A., The Application of the Preoperative Image-Guided 3D Visualization Supported by Machine Learning to the Prediction of Organs Reconstruction During Pancreaticoduodenectomy via a Head-Mounted Displays, International Conference on eXtended Reality, XR SALENTO 2023, 2023-09-06/09-09, Lecce (IT), DOI: 10.1007/978-3-031-43401-3_21, No.14218, pp.321-344, 2023

Abstract:
Early pancreatic cancer diagnosis and therapy drastically increase the chances of survival. Tumor visualization using CT scan images is an important part of these processes. In this paper, we apply Mixed Reality (MR) and Artificial Intelligence, in particular, Machine Learning (ML) to prepare image-guided 3D models of pancreatic cancer in a population of oncology patients. Object detection was based on the convolution neural network, i.e. the You Only Look Once (YOLO) version 7 algorithm, while the semantic segmentation has been done with the 3D-UNET algorithm. Next, the 3D holographic visualization of this model as an interactive, MR object was performed using the Microsoft HoloLens2. The results indicated that the proposed MR and ML-based approach can precisely segment the pancreas along with suspected lesions, thus providing a reliable tool for diagnostics and surgical planning, especially when considering organ reconstruction during pancreaticoduodenectomy.

Keywords:
Extended Reality, Mixed Reality, Augmented Reality, Head-Mounted Displays, Artificial Intelligence, Image-guided surgery

Affiliations:
Proniewska K. - Jagiellonian University (PL)
Kolecki R. - other affiliation
Grochowska A. - other affiliation
Popiela T. - other affiliation
Rogula T. - other affiliation
Malinowski K. - Warsaw University of Technology (PL)
Dołęga-Dołęgowski D. - Jagiellonian University (PL)
Kenig J. - other affiliation
Richter P. - Jagiellonian University (PL)
Dąbrowa J. - other affiliation
Mortada M.J. - other affiliation
van Dam P. - PEACS BV, Nieuwerbrug (NL)
Pręgowska A. - IPPT PAN

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