Pathologists have several tasks to perform when examining anatomical specimens. XR Pathology is an application designed to support this need. In fact, the application allows speech synthesis, viewing patient data, and integrating photos and videos of the materials to be examined. Allowing pathologists to handle surgical materials and interact with the application without needing clean hands facilitates computerized transcription and allows them to focus on more specialized tasks. As a result, patients benefit from faster diagnoses. The design and development process was both collaborative and user-centered. The present usability test was performed within a sample of 8 medicians, and objective and subjective measures were collected. Results showed a preference for voice interaction, positive usability, and user experience feedback. In particular, participants considered the application easy to use and learn. However, improvements are needed in task accuracy and system responsiveness. Future steps include finalizing the user journey on Hololens 2, completing regulatory processes in compliance with EU regulations for medical devices, and exploring new hardware to overcome current technological limitations. Additionally, incorporating AI for image analysis is planned. These enhancements aim to ensure the application meets medical professionals’ needs and adapts to cutting-edge technology and regulatory standards.

Mondellini, M., Menghi, F., Sacco, M., Greci, L., Transforming Anatomopathology with XR Pathology: A Usability Study on HoloLens Integration, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), (LECCE -- ITA, 04-07 September 2024), Springer Science and Business Media Deutschland GmbH, GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND 2024:<<LECTURE NOTES IN COMPUTER SCIENCE>>,15028 69-86. [10.1007/978-3-031-71704-8_6] [https://hdl.handle.net/10807/313623]

Transforming Anatomopathology with XR Pathology: A Usability Study on HoloLens Integration

Mondellini, Marta
Primo
;
2024

Abstract

Pathologists have several tasks to perform when examining anatomical specimens. XR Pathology is an application designed to support this need. In fact, the application allows speech synthesis, viewing patient data, and integrating photos and videos of the materials to be examined. Allowing pathologists to handle surgical materials and interact with the application without needing clean hands facilitates computerized transcription and allows them to focus on more specialized tasks. As a result, patients benefit from faster diagnoses. The design and development process was both collaborative and user-centered. The present usability test was performed within a sample of 8 medicians, and objective and subjective measures were collected. Results showed a preference for voice interaction, positive usability, and user experience feedback. In particular, participants considered the application easy to use and learn. However, improvements are needed in task accuracy and system responsiveness. Future steps include finalizing the user journey on Hololens 2, completing regulatory processes in compliance with EU regulations for medical devices, and exploring new hardware to overcome current technological limitations. Additionally, incorporating AI for image analysis is planned. These enhancements aim to ensure the application meets medical professionals’ needs and adapts to cutting-edge technology and regulatory standards.
2024
Inglese
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
International Conference on eXtended Reality, XR Salento 2024
LECCE -- ITA
4-set-2024
7-set-2024
9783031717031
Springer Science and Business Media Deutschland GmbH
Mondellini, M., Menghi, F., Sacco, M., Greci, L., Transforming Anatomopathology with XR Pathology: A Usability Study on HoloLens Integration, in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), (LECCE -- ITA, 04-07 September 2024), Springer Science and Business Media Deutschland GmbH, GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND 2024:<<LECTURE NOTES IN COMPUTER SCIENCE>>,15028 69-86. [10.1007/978-3-031-71704-8_6] [https://hdl.handle.net/10807/313623]
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10807/313623
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