Abstract
Asymmetry is a crucial characteristic of bilateral mammograms (Bi-MG) when abnormalities are developing. It is widely utilized by radiologists for diagnosis. The question of “what the symmetrical Bi-MG would look like when the asymmetrical abnormalities have been removed ?” has not yet received strong attention in the development of algorithms on mammograms. Addressing this question could provide valuable insights into mammographic anatomy and aid in diagnostic interpretation. Hence, we propose a novel framework, DisAsymNet, which utilizes asymmetrical abnormality transformer guided self-adversarial learning for disentangling abnormalities and symmetric Bi-MG. At the same time, our proposed method is partially guided by randomly synthesized abnormalities. We conduct experiments on three public and one in-house dataset, and demonstrate that our method outperforms existing methods in abnormality classification, segmentation, and localization tasks. Additionally, reconstructed normal mammograms can provide insights toward better interpretable visual cues for clinical diagnosis. The code will be accessible to the public.
Original language | English |
---|---|
Title of host publication | Medical Image Computing and Computer Assisted Intervention – MICCAI 2023 - 26th International Conference, Proceedings |
Editors | Hayit Greenspan, Anant Madabhushi, Parvin Mousavi, Septimiu Salcudean, James Duncan, Tanveer Syeda-Mahmood, Russell Taylor |
Publisher | Springer Verlag |
Pages | 57-67 |
Number of pages | 11 |
Volume | 14226 |
Edition | 7 |
ISBN (Electronic) | 978-3-031-43990-2 |
ISBN (Print) | 9783031439896 |
DOIs | |
Publication status | Published - 1 Jan 2023 |
Event | 26th International Conference on Medical Image Computing and Computer Assisted Intervention - Vancouver, Canada Duration: 8 Oct 2023 → 12 Oct 2023 Conference number: 26 https://conferences.miccai.org/2023/en/ |
Publication series
Series | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
---|---|
Volume | 14226 LNCS |
ISSN | 0302-9743 |
Conference
Conference | 26th International Conference on Medical Image Computing and Computer Assisted Intervention |
---|---|
Abbreviated title | MICCAI 2023 |
Country/Territory | Canada |
City | Vancouver |
Period | 8/10/23 → 12/10/23 |
Internet address |
Keywords
- Asymmetric transformer
- Bilateral mammogram
- Disentanglement
- Self-adversarial learning
- Synthesis