A self-guided anomaly detection-inspired few-shot segmentation network. - Suaiba Amina Salahuddin; Stine Hansen; Srishti Gautam; Michael Kampffmeyer; Robert Jenssen (CVCS, 2022)

ProtoVAE: A Trustworthy Self-Explainable Prototypical Variational Model. - Srishti Gautam; Ahcène Boubekki; Stine Hansen; Suaiba Amina Salahuddin; Robert Jenssen; Marina M.-C. Höhne; Michael Kampffmeyer (NeurIPS, 2022)

ADNet++: A few-shot learning framework for multi-class medical image volume segmentation with uncertainty-guided feature refinement. - Stine Hansen; Srishti Gautam; Suaiba Amina Salahuddin; Michael Kampffmeyer; Robert Jenssen (Medical Image Anal., 2023)

Assessing the Efficacy of Multi-task Learning in Mammographic Density Classification: A Study on Class Imbalance and Model Performance. - Suaiba Amina Salahuddin; Elisabeth Wetzer; Kristoffer Wickstrøm; Solveig Thrun; Michael Kampffmeyer; Robert Jenssen (SCIA (2), 2025)

Reconsidering Explicit Longitudinal Mammography Alignment for Enhanced Breast Cancer Risk Prediction. - Solveig Thrun; Stine Hansen; Zijun Sun; Nele Blum; Suaiba Amina Salahuddin; Kristoffer Wickstrøm; Elisabeth Wetzer; Robert Jenssen; Maik Stille; Michael Kampffmeyer (CoRR, 2025)