Abstract
Mammography is a standard tool for breast cancer diagnosis. In current clinical practice, typically two mammograms of each breast are taken from different angles. A fundamental step when using ipsilateral mammograms for the diagnosis of breast cancer, is the identification of corresponding locations/structures in both views, which is a very challenging task due to the projective nature of the images and the different compression parameters used for each view. In this contribution, four different approaches for the estimation of corresponding locations in ipsilateral mammograms are systematically compared using 46 mammogram pairs (50 point-to-point correspondences). The evaluation includes simple heuristic methods (annular bands and straight strips) as well as methods based on geometric and physically motivated breast compression models, which aim to simulate the mammogram acquisition process. The evaluation results show that on average no significant differences exist between the estimation accuracies obtained using the simple heuristic methods and the more involved compression models. However, the results of this study indicate the potential of a method that optimally combines the different approaches.
| Originalsprache | Englisch |
|---|---|
| Titel | Medical Imaging 2015: Computer-Aided Diagnosis |
| Redakteure/-innen | Georgia D. Tourassi, Lubomir M. Hadjiiski |
| Band | 9414 |
| Erscheinungsdatum | 20.03.2015 |
| Seiten | 94142B |
| ISBN (Print) | 9781628415049 |
| DOIs | |
| Publikationsstatus | Veröffentlicht - 20.03.2015 |
| Veranstaltung | SPIE Medical Imaging 2015: Computer-Aided Diagnosis - Renaissance Orlando at SeaWorld, Orlando, USA / Vereinigte Staaten Dauer: 21.02.2015 → 26.02.2015 https://spie.org/conferences-and-exhibitions/past-conferences-and-exhibitions/medical-imaging-2015 |
UN SDGs
Dieser Output leistet einen Beitrag zu folgendem(n) Ziel(en) für nachhaltige Entwicklung
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SDG 3 – Gesundheit und Wohlergehen
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SDG 9 – Industrie, Innovation und Infrastruktur
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