Breast-lesions characterization using Quantitative Ultrasound features of peritumoral tissue

Ziemowit Klimonda; Piotr Karwat; Katarzyna Dobruch‐Sobczak; Hanna Piotrzkowska‐Wróblewska; Jerzy Litniewski

doi:10.1038/s41598-019-44376-z

ScienceGate Book Chapters

JOURNAL ARTICLE

Breast-lesions characterization using Quantitative Ultrasound features of peritumoral tissue

Ziemowit Klimonda Piotr Karwat Katarzyna Dobruch‐Sobczak Hanna Piotrzkowska‐Wróblewska Jerzy Litniewski

Year: 2019 Journal: Scientific Reports Vol: 9 (1)Pages: 7963-7963 Publisher: Nature Portfolio

DOI: 10.1038/s41598-019-44376-z

Get Full-Text PDF Get Analytical Report

Keywords:

Nakagami distribution Biopsy Pathology Medicine Ultrasound Histopathology Breast tissue Breast cancer Radiology Pattern recognition (psychology) Artificial intelligence Computer science Mathematics Cancer Internal medicine Statistics

Metrics

Cited By

6.56

FWCI (Field Weighted Citation Impact)

Refs

0.96

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Ultrasound Imaging and Elastography

Health Sciences → Medicine → Radiology, Nuclear Medicine and Imaging

AI in cancer detection

Physical Sciences → Computer Science → Artificial Intelligence

Breast Lesions and Carcinomas

Health Sciences → Medicine → Pathology and Forensic Medicine

Breast-lesions characterization using Quantitative Ultrasound features of peritumoral tissue

Metrics

Citation History

Topics

Related Documents

Quantitative ultrasound examination of peritumoral tissue improves classification of breast lesions

Quantitative Characterization of Tissue Using Ultrasound

Quantitative characterization of atherosclerotic lesions using ultrasound

Breast-Lesion Characterization using Textural Features of Quantitative Ultrasound Parametric Maps

Quantitative evaluation of peripheral tissue elasticity for ultrasound-detected breast lesions