Area of research
Cancer Research · Pathology and Forensic Medicine
Research interest
Research interests include Breast Cancer Treatment Studies, Breast Lesions and Carcinomas, Breast Implant and Reconstruction, and AI in cancer detection.
Best Practice Guideline – Empfehlungen der DEGUM zur Durchführung und Beurteilung der Mammasonografie
Deep Learning Model for Breast Shear Wave Elastography to Improve Breast Cancer Diagnosis (INSPiRED 006): An International, Multicenter Analysis
Best Practice Guidelines - DEGUM Recommendations on Breast Ultrasound.
Deep Learning Model for Breast Shear Wave Elastography to Improve Breast Cancer Diagnosis (INSPiRED 006): An International, Multicenter Analysis.
Correction: Best Practice Guidelines - DEGUM Recommendations on Breast Ultrasound.
Correction: Best Practice Guidelines - DEGUM Recommendations on Breast Ultrasound.
Best Practice Guidelines - DEGUM Recommendations on Breast Ultrasound.
Incidence and Risk Assessment of Capsular Contracture in Breast Cancer Patients following Post-Mastectomy Radiotherapy and Implant-Based Reconstruction
Incidence and Risk Assessment of Capsular Contracture in Breast Cancer Patients following Post-Mastectomy Radiotherapy and Implant-Based Reconstruction.
Shear-wave elastography as a supplementary tool for axillary staging in patients undergoing breast cancer diagnosis.
Breast-conserving surgery is not associated with increased local recurrence in patients with early-stage node-negative triple-negative breast cancer treated with neoadjuvant chemotherapy
Machine Learning to Predict the Individual Risk of Treatment-Relevant Toxicity for Patients With Breast Cancer Undergoing Neoadjuvant Systemic Treatment
Machine Learning to Predict the Individual Risk of Treatment-Relevant Toxicity for Patients With Breast Cancer Undergoing Neoadjuvant Systemic Treatment.
Postoperative Bildgebung – was ist erforderlich, was überflüssig?
Deep learning to predict breast cancer sentinel lymph node status on INSEMA histological images
Imaging of lumpectomy surface with large field-of-view confocal laser scanning microscopy ‘Histolog® scanner’ for breast margin assessment in comparison with conventional specimen radiography
The Potential of Shear Wave Elastography to Reduce Unnecessary Biopsies in Breast Cancer Diagnosis: An International, Diagnostic, Multicenter Trial.
Deep learning to predict breast cancer sentinel lymph node status on INSEMA histological images.
Prevalence of Pathogenic Germline Variants in Women with Non-Familial Unilateral Triple-Negative Breast Cancer
Ultrasound Radiomics Features to Identify Patients With Triple‐Negative Breast Cancer
Noninferiority of Local Control and Comparable Toxicity of Intensity Modulated Radiation Therapy With Simultaneous Integrated Boost in Breast Cancer: 5-Year Results of the IMRT-MC2 Phase III Trial
Minimally Invasive Breast Biopsy After Neoadjuvant Systemic Treatment to Identify Breast Cancer Patients with Residual Disease for Extended Neoadjuvant Treatment: A New Concept
Prevalence of Pathogenic Germline Variants in Women with Non-Familial Unilateral Triple-Negative Breast Cancer.
Potential of Lesion-to-Fat Elasticity Ratio Measured by Shear Wave Elastography to Reduce Benign Biopsies in BI-RADS 4 Breast Lesions.
Breast elastography—ready for prime time?
Abstract PD15-06: PD15-06 Pathologic complete response and breast-conserving surgery are associated with improved prognosis in patients with early-stage triple-negative breast cancer treated with neoadjuvant chemotherapy
Deep Learning to Predict Breast Cancer Sentinel Lymph Node Status on Insema Histological Images
Conventional specimen radiography in breast-conserving therapy: a useful tool for intraoperative margin assessment after neoadjuvant therapy?
Best Practice Guideline - DEGUM Recommendations on Breast Ultrasound.
Clinical prototype implementation enabling an improved day-to-day mammography compression.