34 citations · 48 across the 7 of their papers we have counts for
7 papers
RADIFUSION: A multi-radiomics deep learning based breast cancer risk prediction model using sequential mammographic images with image attention and bilateral asymmetry refinement
Hong Hui Yeoh, Andrea Liew, Raphaël Phan +5
Breast cancer is a significant public health concern and early detection is critical for triaging high risk patients. Sequential screening mammograms can provide important spatiote…
Visual Detection of Personal Protective Equipment and Safety Gear on Industry Workers
Jonathan Karlsson, Fredrik Strand, Josef Bigun +3
Workplace injuries are common in today's society due to a lack of adequately worn safety equipment. A system that only admits appropriately equipped personnel can be created to imp…
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…
PatchDropout: Economizing Vision Transformers Using Patch Dropout
Yue Liu, Christos Matsoukas, Fredrik Strand +2
Vision transformers have demonstrated the potential to outperform CNNs in a variety of vision tasks. But the computational and memory requirements of these models prohibit their us…
Development and evaluation of a 3D annotation software for interactive COVID-19 lesion segmentation in chest CT
Simone Bendazzoli, Irene Brusini, Mehdi Astaraki +7
Segmentation of COVID-19 lesions from chest CT scans is of great importance for better diagnosing the disease and investigating its extent. However, manual segmentation can be very…
Adding Seemingly Uninformative Labels Helps in Low Data Regimes
Christos Matsoukas, Albert Bou I Hernandez, Yue Liu +8
Evidence suggests that networks trained on large datasets generalize well not solely because of the numerous training examples, but also class diversity which encourages learning o…
Decoupling Inherent Risk and Early Cancer Signs in Image-based Breast Cancer Risk Models
Yue Liu, Hossein Azizpour, Fredrik Strand +1
The ability to accurately estimate risk of developing breast cancer would be invaluable for clinical decision-making. One promising new approach is to integrate image-based risk mo…