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 2 Features measured by different methods

Analysis method	Feature
ADC	ADC_min
	ADC_max
	ADC_mean
Gray level co-occurrence matrix	Dissimilarity
	Sum average
	Difference variance
	Information correlation
Gray level run-length matrix	Gray level nonuniformity
	Run percentage
	Long run low gray level emphasis
	Run-length nonuniformity
Wavelet	SymletL
	SymletH
	SymletV
	SymletD

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.