Work

Combining Radiomics and Autoencoders to Distinguish Benign and Malignant Breast Tumors on US Images

Year: 2024

Type: article

Abstract: Combining classical radiomics and autoencoder-based features extracted from tumor bounding boxes improves US-based categorization of benign and malignant breast tumors compared with segmentation-based approaches.

Source: Radiology

DOI: 10.1148/radiol.232554

Authors: Zuzanna Anna Magnuska, Rijo Roy, Moritz Palmowski, Matthias Kohlen, Brigitte Sophia Winkler, Tatjana Pfeil, Peter Boor, Volkmar Schulz, Katja Krauss, Elmar Stickeler, Fabian Kiessling

Institutions: Universitätsklinikum Aachen, RWTH Aachen University

Language: English

Topic: Radiomics and Machine Learning in Medical Imaging

Subfield: Radiology, Nuclear Medicine and Imaging

Field: Medicine

Domain: Health Sciences

SDG: Good health and well-being

Open Access status: hybrid

OpenAlex ID: W4402392576

FWCI: 8.027

Cites: 33

Cited by: 35

Related to: 10