15 citations · 25 across the 4 of their papers we have counts for
4 papers
MammoTracker: Mask-Guided Lesion Tracking in Temporal Mammograms
Xuan Liu, Yinhao Ren, Marc D. Ryser +2
Accurate lesion tracking in temporal mammograms is essential for monitoring breast cancer progression and facilitating early diagnosis. However, automated lesion correspondence acr…
Interpretable Mammographic Image Classification using Case-Based Reasoning and Deep Learning
Alina Jade Barnett, Fides Regina Schwartz, Chaofan Tao +4
When we deploy machine learning models in high-stakes medical settings, we must ensure these models make accurate predictions that are consistent with known medical science. Inhere…
IAIA-BL: A Case-based Interpretable Deep Learning Model for Classification of Mass Lesions in Digital Mammography
Alina Jade Barnett, Fides Regina Schwartz, Chaofan Tao +4
Interpretability in machine learning models is important in high-stakes decisions, such as whether to order a biopsy based on a mammographic exam. Mammography poses important chall…
Mask Embedding in conditional GAN for Guided Synthesis of High Resolution Images
Yinhao Ren, Zhe Zhu, Yingzhou Li +1
Recent advancements in conditional Generative Adversarial Networks (cGANs) have shown promises in label guided image synthesis. Semantic masks, such as sketches and label maps, are…