Prediction of Clinical Pathologic Prognostic Factors for Rectal Adenocarcinoma: Volumetric Texture Analysis Based on Apparent Diffusion Coefficient Maps

Texture analysis has been used to characterize and measure tissue heterogeneity in medical images. The purpose of this study was to investigate the potential of texture features derived from apparent diffusion coefficient (ADC) maps, to serve as imaging markers for predicting important histopatholog...

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Veröffentlicht in:	Journal of medical systems Jg. 43; H. 12; S. 331
Hauptverfasser:	Lu, Zhihua, Wang, Lei, Xia, Kaijian, Jiang, Heng, Weng, Xiaoyan, Jiang, Jianlong, Wu, Mei
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	New York Springer US 01.12.2019 Springer Nature B.V
Schlagworte:	Adenocarcinoma Adenocarcinoma - diagnostic imaging Adenocarcinoma - pathology Adult Aged Aged, 80 and over Algorithms Cancer Colorectal cancer Diffusion Diffusion coefficient Diffusion Magnetic Resonance Imaging - methods Distributed Analytics and Deep Learning in Health Care Energy Entropy Female Health Informatics Health Sciences Heterogeneity Histograms Humans Image & Signal Processing Image Interpretation, Computer-Assisted - methods Kurtosis Logistic Models Magnetic resonance imaging Male Medical imaging Medical prognosis Medicine Medicine & Public Health Middle Aged Neoplasm Grading Predictions Prognosis Prospective Studies Rectal Neoplasms - diagnostic imaging Rectal Neoplasms - pathology Rectum Regression analysis ROC Curve Skewness Statistical analysis Statistics for Life Sciences Texture Tumors Diffusion-weighted imaging Texture analysis Rectal cancer Apparent diffusion coefficient
ISSN:	0148-5598, 1573-689X, 1573-689X
Online-Zugang:	Volltext
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