Automatic Classification for Pathological Prostate Images Based on Fractal Analysis

Accurate grading for prostatic carcinoma in pathological images is important to prognosis and treatment planning. Since human grading is always time-consuming and subjective, this paper presents a computer-aided system to automatically grade pathological images according to Gleason grading system wh...

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Veröffentlicht in:	IEEE transactions on medical imaging 2009-07, Vol.28 (7), p.1037-1050
Hauptverfasser:	Huang, Po-Whei, Lee, Cheng-Hsiung
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Artificial Intelligence Bayes Theorem Bayesian methods Classification Classifiers Evaluation Feature extraction Fractal analysis fractal dimension Fractals Gleason grading Histocytochemistry - methods Humans Image analysis Image texture analysis Male Microscopy Neoplasm Staging Path planning Pathology Pattern Recognition, Automated - methods Prostate prostate image prostatic carcinoma Prostatic Neoplasms - pathology Quality Reproducibility of Results Studies Support vector machine classification Support vector machines Texture
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