Projects per year
Abstract
More than 55,000 people world-wide die from Cardiovascular Disease (CVD) each day. Calcification of the abdominal aorta is an established marker of asymptomatic CVD. It can be observed on scans taken for vertebral fracture assessment from Dual Energy X-ray Absorptiometry machines. Assessment of Abdominal Aortic Calcification (AAC) and timely intervention may help to reinforce public health messages around CVD risk factors and improve disease management, reducing the global health burden related to CVDs. Our research addresses this problem by proposing a novel and reliable framework for automated “fine-grained” assessment of AAC. Inspired by the vision-to-language models, our method performs sequential scoring of calcified lesions along the length of the abdominal aorta on DXA scans; mimicking the human scoring process.
Original language | English |
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Title of host publication | Medical Image Computing and Computer Assisted Intervention – MICCAI 2022 - 25th International Conference, Proceedings |
Editors | Linwei Wang, Qi Dou, P. Thomas Fletcher, Stefanie Speidel, Shuo Li |
Publisher | Springer Science + Business Media |
Pages | 439-450 |
Number of pages | 12 |
ISBN (Print) | 9783031164361 |
DOIs | |
Publication status | Published - 2022 |
Event | 25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022 - Singapore, Singapore Duration: 18 Sept 2022 → 22 Sept 2022 |
Publication series
Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
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Volume | 13433 LNCS |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022 |
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Country/Territory | Singapore |
City | Singapore |
Period | 18/09/22 → 22/09/22 |
Fingerprint
Dive into the research topics of 'Show, Attend and Detect: Towards Fine-Grained Assessment of Abdominal Aortic Calcification on Vertebral Fracture Assessment Scans'. Together they form a unique fingerprint.Projects
- 1 Finished
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Developing automated methods for evaluating structural vascular disease
Prince, R. (Investigator 01)
NHMRC National Health and Medical Research Council
1/01/20 → 31/12/23
Project: Research