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:	Vincent Chukwudi Chijindu, Chidiebele Udeze, Mamilus Ahaneku, Ijeoma Anarado-Ezika, Kennedy Okafor
Formato:	article
Lenguaje:	EN
Publicado:	Shiraz University of Medical Sciences 2019
Materias:	image hyper-echoic prostate localisation anatomical zones segmentation Medicine R
Acceso en línea:	https://doaj.org/article/1430f87e8d7d49449e55c585af53d88c
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spelling	oai:doaj.org-article:1430f87e8d7d49449e55c585af53d88c2021-11-14T08:42:28ZLocalisation of Zones of Cancer Detection in Prostate Gland Using Ratio Matrix and Radial Scanning of 2D Trans-rectal Ultrasound Images;2783-243010.30476/acrr.2019.45968https://doaj.org/article/1430f87e8d7d49449e55c585af53d88c2019-12-01T00:00:00Zhttps://colorectalresearch.sums.ac.ir/article_45968_4dc02d2b4e8c7d94683bd30f9a172120.pdfhttps://doaj.org/toc/2783-2430Researchers 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%.Vincent Chukwudi ChijinduChidiebele UdezeMamilus AhanekuIjeoma Anarado-EzikaKennedy OkaforShiraz University of Medical Sciencesarticleimagehyper-echoicprostatelocalisationanatomicalzonessegmentationMedicineRENIranian Journal of Colorectal Research, Vol 7, Iss 4, Pp 1-7 (2019)
institution	DOAJ
collection	DOAJ
language	EN
topic	image hyper-echoic prostate localisation anatomical zones segmentation Medicine R
spellingShingle	image hyper-echoic prostate localisation anatomical zones segmentation Medicine R Vincent Chukwudi Chijindu Chidiebele Udeze Mamilus Ahaneku Ijeoma Anarado-Ezika Kennedy Okafor Localisation of Zones of Cancer Detection in Prostate Gland Using Ratio Matrix and Radial Scanning of 2D Trans-rectal Ultrasound Images;
description	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%.
format	article
author	Vincent Chukwudi Chijindu Chidiebele Udeze Mamilus Ahaneku Ijeoma Anarado-Ezika Kennedy Okafor
author_facet	Vincent Chukwudi Chijindu Chidiebele Udeze Mamilus Ahaneku Ijeoma Anarado-Ezika Kennedy Okafor
author_sort	Vincent Chukwudi Chijindu
title	Localisation of Zones of Cancer Detection in Prostate Gland Using Ratio Matrix and Radial Scanning of 2D Trans-rectal Ultrasound Images;
title_short	Localisation of Zones of Cancer Detection in Prostate Gland Using Ratio Matrix and Radial Scanning of 2D Trans-rectal Ultrasound Images;
title_full	Localisation of Zones of Cancer Detection in Prostate Gland Using Ratio Matrix and Radial Scanning of 2D Trans-rectal Ultrasound Images;
title_fullStr	Localisation of Zones of Cancer Detection in Prostate Gland Using Ratio Matrix and Radial Scanning of 2D Trans-rectal Ultrasound Images;
title_full_unstemmed	Localisation of Zones of Cancer Detection in Prostate Gland Using Ratio Matrix and Radial Scanning of 2D Trans-rectal Ultrasound Images;
title_sort	localisation of zones of cancer detection in prostate gland using ratio matrix and radial scanning of 2d trans-rectal ultrasound images;
publisher	Shiraz University of Medical Sciences
publishDate	2019
url	https://doaj.org/article/1430f87e8d7d49449e55c585af53d88c
work_keys_str_mv	AT vincentchukwudichijindu localisationofzonesofcancerdetectioninprostateglandusingratiomatrixandradialscanningof2dtransrectalultrasoundimages AT chidiebeleudeze localisationofzonesofcancerdetectioninprostateglandusingratiomatrixandradialscanningof2dtransrectalultrasoundimages AT mamilusahaneku localisationofzonesofcancerdetectioninprostateglandusingratiomatrixandradialscanningof2dtransrectalultrasoundimages AT ijeomaanaradoezika localisationofzonesofcancerdetectioninprostateglandusingratiomatrixandradialscanningof2dtransrectalultrasoundimages AT kennedyokafor localisationofzonesofcancerdetectioninprostateglandusingratiomatrixandradialscanningof2dtransrectalultrasoundimages
_version_	1718429760139296768

Localisation of Zones of Cancer Detection in Prostate Gland Using Ratio Matrix and Radial Scanning of 2D Trans-rectal Ultrasound Images;

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