82 citations · 205 across the 6 of their papers we have counts for
7 papers · 1 filter
Revisiting Skin Tone Fairness in Dermatological Lesion Classification
Thorsten Kalb, Kaisar Kushibar, Celia Cintas +3
Addressing fairness in lesion classification from dermatological images is crucial due to variations in how skin diseases manifest across skin tones. However, the absence of skin t…
medigan: a Python library of pretrained generative models for medical image synthesis
Richard Osuala, Grzegorz Skorupko, Noussair Lazrak +9
Synthetic data generated by generative models can enhance the performance and capabilities of data-hungry deep learning models in medical imaging. However, there is (1) limited ava…
High-resolution synthesis of high-density breast mammograms: Application to improved fairness in deep learning based mass detection
Lidia Garrucho, Kaisar Kushibar, Richard Osuala +7
Computer-aided detection systems based on deep learning have shown good performance in breast cancer detection. However, high-density breasts show poorer detection performance sinc…
Sharing Generative Models Instead of Private Data: A Simulation Study on Mammography Patch Classification
Zuzanna Szafranowska, Richard Osuala, Bennet Breier +3
Early detection of breast cancer in mammography screening via deep-learning based computer-aided detection systems shows promising potential in improving the curability and mortali…
Data synthesis and adversarial networks: A review and meta-analysis in cancer imaging
Richard Osuala, Kaisar Kushibar, Lidia Garrucho +6
Despite technological and medical advances, the detection, interpretation, and treatment of cancer based on imaging data continue to pose significant challenges. These include inte…
Quality analysis of DCGAN-generated mammography lesions
Basel Alyafi, Oliver Diaz, Joan C Vilanova +2
Medical image synthesis has gained a great focus recently, especially after the introduction of Generative Adversarial Networks (GANs). GANs have been used widely to provide anatom…
DCGANs for Realistic Breast Mass Augmentation in X-ray Mammography
Basel Alyafi, Oliver Diaz, Robert Marti
Early detection of breast cancer has a major contribution to curability, and using mammographic images, this can be achieved non-invasively. Supervised deep learning, the dominant…