4 citations · 7 across the 2 of their papers we have counts for
3 papers · 1 filter
MammoDG: Generalisable Deep Learning Breaks the Limits of Cross-Domain Multi-Center Breast Cancer Screening
Yijun Yang, Shujun Wang, Lihao Liu +4
Breast cancer is a major cause of cancer death among women, emphasising the importance of early detection for improved treatment outcomes and quality of life. Mammography, the prim…
Beyond Fine-tuning: Classifying High Resolution Mammograms using Function-Preserving Transformations
Tao Wei, Angelica I Aviles-Rivero, Shuo Wang +4
The task of classifying mammograms is very challenging because the lesion is usually small in the high resolution image. The current state-of-the-art approaches for medical image c…
MAMMO: A Deep Learning Solution for Facilitating Radiologist-Machine Collaboration in Breast Cancer Diagnosis
Trent Kyono, Fiona J. Gilbert, Mihaela van der Schaar
With an aging and growing population, the number of women requiring either screening or symptomatic mammograms is increasing. To reduce the number of mammograms that need to be rea…