Electrical parameter profiles of human breast images can be used to simulate and analyze the anticipated effects on tissue from its interaction with electromagnetic fields involved in the cancer treatment exposure. In part, the success of this approach depends on the accuracy and precision in identifying the different tissue types. In this work, we propose two methods of segmenting human breast images with malignant tumors. The first method of algorithmic partitioning of the image involves manual color-edge contouring of the tissues using a cursor and subsequent identification of the tissue types. For the second method, MRI T1 values and thresholds are used to perform segmentation and we investigate the potential of incorporating edge detection. The first method is effective, while the second lacks precision, but eliminates the need of manual contouring. The images are imported as BMP files into SEMCAD, an electromagnetic simulation tool based on finite-difference time-domain method, which recognizes the grouped tissues and creates a model of the image. The model allows the user to easily assign electrical parameter values to the grouped tissues, according to the measured values reported in the literature.
| Identifer | oai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:QMM.116044 |
| Date | January 2008 |
| Creators | Al-Roubaie, Zahra. |
| Publisher | McGill University |
| Source Sets | Library and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada |
| Language | English |
| Detected Language | English |
| Type | Electronic Thesis or Dissertation |
| Format | application/pdf |
| Coverage | Master of Engineering (Department of Electrical and Computer Engineering.) |
| Rights | All items in eScholarship@McGill are protected by copyright with all rights reserved unless otherwise indicated. |
| Relation | alephsysno: 002839815, proquestno: AAIMR66982, Theses scanned by UMI/ProQuest. |
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