Paper
13 March 2006 Uterine fibroid segmentation and volume measurement on MRI
Jianhua Yao, David Chen, Wenzhu Lu, Ahalya Premkumar
Author Affiliations +
Abstract
Uterine leiomyomas are the most common pelvic tumors in females. The efficacy of medical treatment is gauged by shrinkage of the size of these tumors. In this paper, we present a method to robustly segment the fibroids on MRI and accurately measure the 3D volume. Our method is based on a combination of fast marching level set and Laplacian level set. With a seed point placed inside the fibroid region, a fast marching level set is first employed to obtain a rough segmentation, followed by a Laplacian level set to refine the segmentation. We devised a scheme to automatically determine the parameters for the level set function and the sigmoid function based on pixel statistics around the seed point. The segmentation is conducted on three concurrent views (axial, coronal and sagittal), and a combined volume measurement is computed to obtain a more reliable measurement. We carried out extensive tests on 13 patients, 25 MRI studies and 133 fibroids. The segmentation result was validated against manual segmentation defined by experts. The average segmentation sensitivity (true positive fraction) among all fibroids was 84.6%, and the average segmentation specificity (1-false positive fraction) was 84.3%.
© (2006) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Jianhua Yao, David Chen, Wenzhu Lu, and Ahalya Premkumar "Uterine fibroid segmentation and volume measurement on MRI", Proc. SPIE 6143, Medical Imaging 2006: Physiology, Function, and Structure from Medical Images, 614322 (13 March 2006); https://doi.org/10.1117/12.653856
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CITATIONS
Cited by 14 scholarly publications.
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KEYWORDS
Image segmentation

Magnetic resonance imaging

Anisotropic diffusion

Interfaces

Image filtering

Tumors

Anisotropic filtering

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