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ECR 2019 / C-1351
Radiomic's data correlated with breast carcinoma in mammograms: a retrospective review
Congress: ECR 2019
Poster No.: C-1351
Type: Scientific Exhibit
Keywords: Breast, Computer applications, Artificial Intelligence, Mammography, RIS, Image manipulation / Reconstruction, Screening, Statistics, Biopsy, Cancer, Image verification, Pathology
Authors: F. Leone1, A. Presazzi2, M. Cellina1, M. A. Orsi1, G. Oliva1; 1Milan/IT, 2PAVIA, IT/IT
DOI:10.26044/ecr2019/C-1351

References

Quantitative texture analysis: robustness of radiomics across two digital mammography manufacturers' systems.

Mendel KR, Li H, Lan L, Cahill CM, Rael V, Abe H, Giger ML.

 

Radiomics based detection and characterization of suspicious lesions on full field digital mammograms.

Sapate SG, Mahajan A, Talbar SN, Sable N, Desai S, Thakur M.

 

Added Value of Radiomics on Mammography for Breast Cancer Diagnosis: A Feasibility Study.

Mao N, Yin P, Wang Q, Liu M, Dong J, Zhang X, Xie H, Hong N.

 

Radiomic Phenotypes of Mammographic Parenchymal Complexity: Toward Augmenting Breast Density in Breast Cancer Risk Assessment.

Kontos D, Winham SJ, Oustimov A, Pantalone L, Hsieh MK, Gastounioti A, Whaley DH, Hruska CB, Kerlikowske K, Brandt K, Conant EF, Vachon CM.

 

Precision Medicine and Radiogenomics in Breast Cancer: New Approaches toward Diagnosis and Treatment.

Pinker K, Chin J, Melsaether AN, Morris EA, Moy L.

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