PGMI.Vision: A Mobile Application for Breast Mammographic Image Quality Evaluation with Usability Analysis

The PGMI classification approach is used in Malaysia to assess mammography quality. However, the PGMI criteria lack objectivity and clear definitions, leading to inconsistent evaluations by different readers. This challenge ensures that all mammography facilities fulfil the basic quality criteria. This study aims to develop a mobile application for objective mammography quality assessment and usability evaluation. Figma was utilized as a design tool for this project to create the PGMI mobile application, called PGMI.Vision, due to its interactive design capabilities and collaborative features. The app includes two important mammography views: craniocaudal (CC) and mediolateral oblique (MLO) each breast, resulting in a set of four images. The study involved 27 participants and used the Usefulness, Satisfaction, and Ease of Use (USE) Questionnaire for evaluation. Usability testing showed the average score for Usefulness was 81.67%, Ease-of-Use was 81.82%, Ease of Learning was 80.93%, and Satisfaction was 79.68%. The overall average score was 81.02%, which exceeds typical benchmarks in USE Questionnaire studies, indicating high user satisfaction and usability. These high scores suggest PGMI.Vision is user-friendly and exhibit significant potential for future use.

Authors

Institutions

Publication Details

Journal
Journal of Medical Device Technology
Published
2024-12-30
DOI
https://doi.org/10.11113/jmeditec.v3.63
Citations
1
Primary Topic
Global Cancer Incidence and Screening
Type
article
Field-Weighted Citation Impact
0.28

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

PGMI.Vision: A Mobile Application for Breast Mammographic Image Quality Evaluation with Usability Analysis

Mariaulpa Sahalan, Nur Farisha Hanna Hamizun, Syakirah Athirah Abdulla Hamid, Wan Siti Khadijah Wan Mustaffa Fikr et al.
1 citations
Journal of Medical Device Technology
Global Cancer Incidence and Screening
0.28
article

PGMI.Vision: A Mobile Application for Breast Mammographic Image Quality Evaluation with Usability Analysis

Mariaulpa Sahalan, Nur Farisha Hanna Hamizun, Syakirah Athirah Abdulla Hamid, Wan Siti Khadijah Wan Mustaffa Fikr, Fatin Liyana Khairi, Mahdi Osman Abdille, Aulia Salma, Nur Afifah Zahidah Jais, Turki Salem Ahmed al-Babakri, Aqilah Hannani Anil Husna
article en
1 citations

Abstract

The PGMI classification approach is used in Malaysia to assess mammography quality. However, the PGMI criteria lack objectivity and clear definitions, leading to inconsistent evaluations by different readers. This challenge ensures that all mammography facilities fulfil the basic quality criteria. This study aims to develop a mobile application for objective mammography quality assessment and usability evaluation. Figma was utilized as a design tool for this project to create the PGMI mobile application, called PGMI.Vision, due to its interactive design capabilities and collaborative features. The app includes two important mammography views: craniocaudal (CC) and mediolateral oblique (MLO) each breast, resulting in a set of four images. The study involved 27 participants and used the Usefulness, Satisfaction, and Ease of Use (USE) Questionnaire for evaluation. Usability testing showed the average score for Usefulness was 81.67%, Ease-of-Use was 81.82%, Ease of Learning was 80.93%, and Satisfaction was 79.68%. The overall average score was 81.02%, which exceeds typical benchmarks in USE Questionnaire studies, indicating high user satisfaction and usability. These high scores suggest PGMI.Vision is user-friendly and exhibit significant potential for future use.

Journal of Medical Device TechnologyVol. 3(2)
University of Technology Malaysia (MY)
Universiti Teknologi Malaysia
Partnerships for the goals
Openalex Percentile: Top 33%
Global Cancer Incidence and Screening
0.28
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.