Prediction of different stages of rectal cancer: Texture analysis based on diffusion-weighted images and apparent diffusion coefficient maps

BPG is committed to discovery and dissemination of knowledge

Home / Archive / Volume 26, Issue 17

Peer-Review Report of This Article

CrossCheck and Google Search of This Article

Academic Rules and Norms of This Article

Citation of this article

Corresponding Author of This Article

Research Domain of This Article

Article-Type of This Article

Open-Access Policy of This Article

Times Cited Counts in Google of This Article

Journal Information of This Article

Publication Name

World Journal of Gastroenterology

ISSN

1007-9327

Publisher of This Article

Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

Retrospective Study

World J Gastroenterol. May 7, 2020; 26(17): 2082-2096
Published online May 7, 2020. doi: 10.3748/wjg.v26.i17.2082

Table 6 Spearman correlation coefficients for independent predictors of N-stage

Features	N stage
Features	R_s	P value
DWI_b₌₀
Sum average	-0.188	0.044
Gray level nonuniformity	-0.149	0.038
SymletH	0.211	0.024
DWI_b₌₁₀₀₀
Sum average	-0.209	0.025
Information correlation	-0.187	0.045
Long run low gray level emphasis	-0.223	0.017
SymletH	0.199	0.033
ADC maps
ADC_max	-0.204	0.029
ADC_mean	-0.273	0.003
Information correlation	-0.199	0.033

DWI: Diffusion-weighted imaging; ADC: Apparent diffusion coefficient.

Citation: Yin JD, Song LR, Lu HC, Zheng X. Prediction of different stages of rectal cancer: Texture analysis based on diffusion-weighted images and apparent diffusion coefficient maps. World J Gastroenterol 2020; 26(17): 2082-2096
URL: https://www.wjgnet.com/1007-9327/full/v26/i17/2082.htm
DOI: https://dx.doi.org/10.3748/wjg.v26.i17.2082

Yin JD, Song LR, Lu HC, Zheng X. Prediction of different stages of rectal cancer: Texture analysis based on diffusion-weighted images and apparent diffusion coefficient maps. World J Gastroenterol 2020; 26(17): 2082-2096 [PMID: 32536776 DOI: 10.3748/wjg.v26.i17.2082]

All content on this site: Copyright © 1993-2026 Baishideng Publishing Group Inc, its licensors, and contributors. All rights are reserved, including those for text and data mining, AI training, and similar technologies. For all open access content, the relevant licensing terms apply.