Litcius/Paper detail

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

Zuzanna Magnuska, Rijo Roy, Moritz Palmowski, Matthias Kohlen, B. Sophia Winkler, Tatjana Pfeil, Peter Boor, Volkmar Schulz, Katja Krauss, Elmar Stickeler, Fabian Kießling

2024Radiology28 citationsDOIOpen Access PDF

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.

Topics & Concepts

MedicineRadiomicsBreast imagingRadiologyBI-RADSBreast tumorArtificial intelligenceBreast cancerMammographyCancerInternal medicineComputer scienceRadiomics and Machine Learning in Medical ImagingMRI in cancer diagnosisAI in cancer detection
Combining Radiomics and Autoencoders to Distinguish Benign and Malignant Breast Tumors on US Images | Litcius