Localisation of Zones of Cancer Detection in Prostate Gland Using Ratio Matrix and Radial Scanning of 2D Trans-rectal Ultrasound Images;
Researchers have continued to proffer various solutions to the challenge of delineating from Trans-rectal ultrasound (TRUS) 2D-images of the prostate the regions of desired property. This paper presents an algorithm that categorises the detected regions suspected to be cancerous, hyper-echoic pixels...
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| Autores principales: | , , , , |
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| Formato: | article |
| Lenguaje: | EN |
| Publicado: |
Shiraz University of Medical Sciences
2019
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| Materias: | |
| Acceso en línea: | https://doaj.org/article/1430f87e8d7d49449e55c585af53d88c |
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| Sumario: | Researchers have continued to proffer various solutions to the challenge of delineating from Trans-rectal ultrasound (TRUS) 2D-images of the prostate the regions of desired property. This paper presents an algorithm that categorises the detected regions suspected to be cancerous, hyper-echoic pixels, in the prostate gland from a 2D Trans-rectal Ultrasound images into three zones. The developed algorithm uses radial scanning of the pixels of the prostate gland image from common seed point both to detect and delineate the suspected cancerous pixels into zones, namely peripheral, transition and central, by applying ratios of the anatomical zones of the prostate gland. Expert knowledge, intensity and gradient features were implemented to delineate regions of interest. MATLAB programming tool was used for creating the codes that implemented the algorithms. Samples of TRUS 2D-images of the prostate for patients with raised PSA values (>10 ng/ml) used in a previous work by Award (2007) were used for testing the algorithm. The test results showed that the algorithm could detect zones of the prostate boundary exhibit image properties for cancer cells and also the percentage of malignancy detected in zones agreed with existing research findings. Comparison of detection results with that of an expert radiologist yielded the following performance parameters; accuracy of 88.55% and sensitivity of 71.65%. |
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