Título : |
Computer-aided prostate cancer diagnosis from digitized histopathology: a review on texture-based systems |
Tipo de documento : |
documento electrónico |
Autores : |
Alejandro Vélez Hoyos, |
Fecha de publicación : |
2015 |
Títulos uniformes : |
IEEE Reviews in Biomedical Engineering
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Idioma : |
Inglés (eng) |
Palabras clave : |
Computer-aided diagnosis (CAD) gleason grading histopathology image analysis pattern recognition prostate cancer texture-based CAD systems |
Resumen : |
Prostate cancer (PCa) is currently diagnosed by microscopic evaluation of biopsy samples. Since tissue assessment heavily relies on the pathologists level of expertise and interpretation criteria, it is still a subjective process with high intra- and interobserver variabilities. Computer-aided diagnosis (CAD) may have a major impact on detection and grading of PCa by reducing the pathologists reading time, and increasing the accuracy and reproducibility of diagnosis outcomes. However, the complexity of the prostatic tissue and the large volumes of data generated by biopsy procedures make the development of CAD systems for PCa a challenging task. The problem of automated diagnosis of prostatic carcinoma from histopathology has received a lot of attention. As a result, a number of CAD systems, have been proposed for quantitative image analysis and classification. This review aims at providing a detailed description of selected literature in the field of CAD of PCa, emphasizing the role of texture analysis methods in tissue description. It includes a review of image analysis tools for image preprocessing, feature extraction, classification, and validation techniques used in PCa detection and grading, as well as future directions in pursuit of better texture-based CAD systems. |
Mención de responsabilidad : |
Clara Mosquera-Lopez, Sos Agaian, Alejandro Velez-Hoyos, Ian Thompson |
Referencia : |
IEEE Rev Biomed Eng. 2015;8:98-113. |
DOI (Digital Object Identifier) : |
10.1109/RBME.2014.2340401 |
PMID : |
25055385 |
En línea : |
http://ieeexplore.ieee.org/document/6857992/ |
Enlace permanente : |
https://hospitalpablotobon.cloudbiteca.com/pmb/opac_css/index.php?lvl=notice_display&id=4604 |
Computer-aided prostate cancer diagnosis from digitized histopathology: a review on texture-based systems [documento electrónico] / Alejandro Vélez Hoyos, . - 2015. Obra : IEEE Reviews in Biomedical EngineeringIdioma : Inglés ( eng) Palabras clave : |
Computer-aided diagnosis (CAD) gleason grading histopathology image analysis pattern recognition prostate cancer texture-based CAD systems |
Resumen : |
Prostate cancer (PCa) is currently diagnosed by microscopic evaluation of biopsy samples. Since tissue assessment heavily relies on the pathologists level of expertise and interpretation criteria, it is still a subjective process with high intra- and interobserver variabilities. Computer-aided diagnosis (CAD) may have a major impact on detection and grading of PCa by reducing the pathologists reading time, and increasing the accuracy and reproducibility of diagnosis outcomes. However, the complexity of the prostatic tissue and the large volumes of data generated by biopsy procedures make the development of CAD systems for PCa a challenging task. The problem of automated diagnosis of prostatic carcinoma from histopathology has received a lot of attention. As a result, a number of CAD systems, have been proposed for quantitative image analysis and classification. This review aims at providing a detailed description of selected literature in the field of CAD of PCa, emphasizing the role of texture analysis methods in tissue description. It includes a review of image analysis tools for image preprocessing, feature extraction, classification, and validation techniques used in PCa detection and grading, as well as future directions in pursuit of better texture-based CAD systems. |
Mención de responsabilidad : |
Clara Mosquera-Lopez, Sos Agaian, Alejandro Velez-Hoyos, Ian Thompson |
Referencia : |
IEEE Rev Biomed Eng. 2015;8:98-113. |
DOI (Digital Object Identifier) : |
10.1109/RBME.2014.2340401 |
PMID : |
25055385 |
En línea : |
http://ieeexplore.ieee.org/document/6857992/ |
Enlace permanente : |
https://hospitalpablotobon.cloudbiteca.com/pmb/opac_css/index.php?lvl=notice_display&id=4604 |
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