Auto Contour Initialization of Breast Masses in Contrast Enhanced Breast CT
| Autor: | Harmandeep Kaur, Neeraj Julka |
|---|---|
| Rok vydání: | 2016 |
| Předmět: |
Mathematical optimization
Computer science business.industry media_common.quotation_subject Breast lesion Centroid Initialization Pattern recognition 030218 nuclear medicine & medical imaging 03 medical and health sciences 0302 clinical medicine Level set 030220 oncology & carcinogenesis Contrast (vision) Point (geometry) Segmentation Artificial intelligence business media_common Breast ct |
| Zdroj: | International Journal Of Engineering And Computer Science. |
| ISSN: | 2319-7242 |
| DOI: | 10.18535/ijecs/v5i11.52 |
| Popis: | Dedicated breast CT (bCT) produces high-resolution 3D tomographic images of the breast, fully resolving fibroglandular tissue structures within the breast and allowing for breast lesion detection and assessment in 3D.Various techniques have been used for detecting cancer in women. Previous studies have worked on providing a manual seed point for evaluating the area of tumor. In this study, we present a method for auto initialization of seed point enhancing the quality of detection. First, image enhancement techniques are used which is then followed by detection of circular areas in image and choosing the best out of them. In next step, centroid of the finest circle is used as the seed point. Further, 3D radial-gradient index segmentation is used to obtain a crude initial contour, which is then refined by a 3D level set-based active contour algorithm. The algorithm is run for a number of iterations to get the enhanced results. |
| Databáze: | OpenAIRE |
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