Lars J. Grimm

Deep learning analysis of breast MRIs for prediction of occult invasive disease in ductal carcinoma in situ

2017 · arXiv (Cornell University)

Purpose: To determine whether deep learning-based algorithms applied to breast MR images can aid in the prediction of occult invasive disease following the di- agnosis of ductal carcinoma in situ (DCIS) by core needle biopsy. …

Convolutional encoder-decoder for breast mass segmentation in digital breast tomosynthesis

2018 · Medical Imaging 2018: Computer-Aided Diagnosis

Digital breast tomosynthesis (DBT) is a relatively new modality for breast imaging that can provide detailed assessment of dense tissue within the breast. In the domains of cancer diagnosis, radiogenomics, and resident education, it is …

Multimodal Patient-Specific Registration for Breast Imaging Using Biomechanical Modeling with Reference to AI Evaluation of Breast Tumor Change

2021 · Life

BACKGROUND: The strategy to combat the problem associated with large deformations in the breast due to the difference in the medical imaging of patient posture plays a vital role in multimodal medical image registration with …