in-house-developed matlab based software (MathWorks Inc)
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90
Structured Review
MathWorks Inc
in-house-developed matlab based software
In House Developed Matlab Based Software, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/in-house-developed+matlab+based+software/pmc09139172-85-31-32
Average 90 stars, based on 1 article reviews
In House Developed Matlab Based Software, supplied by MathWorks Inc, used in various techniques. Bioz Stars score: 90/100, based on 1 PubMed citations. ZERO BIAS - scores, article reviews, protocol conditions and more
https://www.bioz.com/product/in-house-developed+matlab+based+software/pmc09139172-85-31-32
Average 90 stars, based on 1 article reviews
in-house-developed matlab based software - by Bioz Stars,
2026-11
90/100 stars
Images
1) Product Images from "Role of Texture Analysis in Oropharyngeal Carcinoma: A Systematic Review of the Literature"
Article Title: Role of Texture Analysis in Oropharyngeal Carcinoma: A Systematic Review of the Literature
Journal: Cancers
doi: 10.3390/cancers14102445
Figure Legend Snippet: Significant features and extraction methods. DSS: disease-specific survival; GLCM: grey level co-occurence matrix; GLNU: Gray level non-uniformity; GLRLM: Gray-level run-length matrix; IQR: interquartile range; LRE: long run emphasis; LRLGE/LRHGE: long-run low/high gray level emphasis; LRLGLE: Long-run low gray-level emphasis; LZE: level zone emphasis feature value; LZHGE: large zone high gray level emphasis; LZLGE: large zone low gray level emphasis; MTV: metabolic tumour volume; NGLDM: neighbourhood gray level difference matrix; OS: overall survival; PFS: progression free survival; SD: standard deviation; SRHGLE: short run high gray level emphasis; SSF: spatial scaling factor; TLG: total lesion glycolysis.
Techniques Used: Extraction, Standard Deviation, Software, Control, Diagnostic Assay, Selection, Imaging
Related Articles
Software:Article Title: Role of Texture Analysis in Oropharyngeal Carcinoma: A Systematic Review of the Literature Article Snippet: Kuno H et al., 2017 [ ] , Semiautomated ROI , Significant predictors of outcome of chemotherapy in patients with SCC were 3 histogram features and 4 gray-level run-length features. , Extraction:Article Title: Role of Texture Analysis in Oropharyngeal Carcinoma: A Systematic Review of the Literature Article Snippet: Kuno H et al., 2017 [ ] , Semiautomated ROI , Significant predictors of outcome of chemotherapy in patients with SCC were 3 histogram features and 4 gray-level run-length features. , Standard Deviation:Article Title: Role of Texture Analysis in Oropharyngeal Carcinoma: A Systematic Review of the Literature Article Snippet: Kuno H et al., 2017 [ ] , Semiautomated ROI , Significant predictors of outcome of chemotherapy in patients with SCC were 3 histogram features and 4 gray-level run-length features. , Control:Article Title: Role of Texture Analysis in Oropharyngeal Carcinoma: A Systematic Review of the Literature Article Snippet: Kuno H et al., 2017 [ ] , Semiautomated ROI , Significant predictors of outcome of chemotherapy in patients with SCC were 3 histogram features and 4 gray-level run-length features. , Diagnostic Assay:Article Title: Role of Texture Analysis in Oropharyngeal Carcinoma: A Systematic Review of the Literature Article Snippet: Kuno H et al., 2017 [ ] , Semiautomated ROI , Significant predictors of outcome of chemotherapy in patients with SCC were 3 histogram features and 4 gray-level run-length features. , Selection:Article Title: Role of Texture Analysis in Oropharyngeal Carcinoma: A Systematic Review of the Literature Article Snippet: Kuno H et al., 2017 [ ] , Semiautomated ROI , Significant predictors of outcome of chemotherapy in patients with SCC were 3 histogram features and 4 gray-level run-length features. , Imaging:Article Title: Role of Texture Analysis in Oropharyngeal Carcinoma: A Systematic Review of the Literature Article Snippet: Kuno H et al., 2017 [ ] , Semiautomated ROI , Significant predictors of outcome of chemotherapy in patients with SCC were 3 histogram features and 4 gray-level run-length features. , |