Automated Segmentation of Breast in 3-D MR Images Using a Robust Atlas
| Autor: | Sharmila Balasingham, Cristina Gallego-Ortiz, Farzad Khalvati, Anne L. Martel |
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| Rok vydání: | 2015 |
| Předmět: |
Adult
Adolescent Computer science Scale-space segmentation Phase congruency Young Adult Imaging Three-Dimensional Atlas (anatomy) medicine Humans Segmentation Computer vision Breast Electrical and Electronic Engineering Models Statistical Radiological and Ultrasound Technology medicine.diagnostic_test business.industry Segmentation-based object categorization Atlas (topology) Pattern recognition Magnetic resonance imaging Image segmentation Middle Aged Magnetic Resonance Imaging Computer Science Applications medicine.anatomical_structure Female Artificial intelligence Mr images business Algorithms Software |
| Zdroj: | IEEE Transactions on Medical Imaging. 34:116-125 |
| ISSN: | 1558-254X 0278-0062 |
| DOI: | 10.1109/tmi.2014.2347703 |
| Popis: | This paper presents a robust atlas-based segmentation (ABS) algorithm for segmentation of the breast boundary in 3-D MR images. The proposed algorithm combines the well-known methodologies of ABS namely probabilistic atlas and atlas selection approaches into a single framework where two configurations are realized. The algorithm uses phase congruency maps to create an atlas which is robust to intensity variations. This allows an atlas derived from images acquired with one MR imaging sequence to be used to segment images acquired with a different MR imaging sequence and eliminates the need for intensity-based registration. Images acquired using a Dixon sequence were used to create an atlas which was used to segment both Dixon images (intra-sequence) and T1-weighted images (inter-sequence). In both cases, highly accurate results were achieved with the median Dice similarity coefficient values of $94\% \pm 4\%$ and $87 \pm 6.5\%$ , respectively. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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