Image Segmentation for the Treatment Planning of Magnetic Resonance-Guided High-Intensity Focused Ultrasound (MRgHIFU) Therapy: A Parametric Study
| Autor: | A. Vargas-Olivares, J. E. Chong-Quero, Samuel Pichardo, Laura Curiel, Octavio Navarro-Hinojosa, Moises Alencastre-Miranda |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
F-measure
Computer science MRgHIFU medicine.medical_treatment 030218 nuclear medicine & medical imaging 03 medical and health sciences 0302 clinical medicine non-parametric statistics Interquartile range medicine General Materials Science Segmentation Radiation treatment planning image segmentation Instrumentation Parametric statistics Fluid Flow and Transfer Processes medicine.diagnostic_test Process Chemistry and Technology General Engineering Magnetic resonance imaging Image segmentation Sagittal plane High-intensity focused ultrasound 3. Good health Computer Science Applications medicine.anatomical_structure 030220 oncology & carcinogenesis ground truth Biomedical engineering |
| Zdroj: | Applied Sciences Volume 9 Issue 24 |
| ISSN: | 2076-3417 |
| DOI: | 10.3390/app9245296 |
| Popis: | In the present research work, image segmentation methods were studied to find internal parameters that provide an efficient identification of the regions of interest in Magnetic Resonance (MR) images used for the therapy planning of High-Intensity Focused Ultrasound (HIFU), a minimally invasive therapeutic method used for selective ablation of tissue. The involved image segmentation methods were threshold, level set and watershed segmentation algorithm with markers (WSAM), and they were applied to transverse and sagittal MR images obtained from an experimental setup of a murine experiment. A parametric study, involving segmentation tests with different values for the internal parameters, was carried out. The F-measure results from the parametric study were analyzed by region using Welch&rsquo s ANOVA followed by post hoc Games-Howell test to determine the most appropriate method for region identification. In transverse images, the threshold method had the best performance for the air region with a F-measure median of 0.9802 (0.9743&ndash 0.9847, interquartile range IQR 0.0104), the WSAM for the tissue, gel-pad, transducer and water region with a F-measure median of 0.9224 (0.8718&ndash 0.9468, IQR 0.075), 0.9553 (0.9496&ndash 0.9606, IQR 0.011), 0.9416 (0.9330&ndash 0.9540, IQR 0.021) and 0.9769 (0.9741&ndash 0.9803, IQR 0.0062), respectively. In sagittal images, threshold method had the best performance for the air region with a F-measure median of 0.9680 (0.9589&ndash 0.9735, IQR 0.0146), the WSAM for the tissue and gel-pad regions with a F-measure median of 0.9241 (0.8870&ndash 0.9426, IQR 0.0556) and 0.9553 (0.9472&ndash 0.9625, IQR 0.0153), respectively, and the Geodesic Active Contours (GAC) method for the transducer and water regions with a F-measure median of 0.9323 (0.9221&ndash 0.9402, IQR 0.0181) and 0.9681 (0.9627&ndash 0.9715, IQR 0.0088), respectively. The present research work integrates preliminary results to generate more efficient procedures of image segmentation for treatment planning of the MRgHIFU therapy. Future work will address the search of an automatic segmentation process, regardless of the experimental setup. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|