cancer

Image analysis with deep learning to predict breast cancer grade, ER status, histologic subtype, and intrinsic subtype

RNA-based, multi-gene molecular assays are available and widely used for patients with ER-positive/HER2-negative breast cancers. However, RNA-based genomic tests can be costly and are not available in many countries. Methods for inferring molecular …

Multiple Instance Learning for Heterogeneous Images: Training a CNN for Histopathology

Multiple instance (MI) learning with a convolutional neural network enables end-to-end training in the presence of weak image-level labels. We propose a new method for aggregating predictions from smaller regions of the image into an image-level …

Patient-Specific Registration of Pre-operative and Post-recurrence Brain Tumor MRI Scans

Registering brain magnetic resonance imaging (MRI) scans containing pathologies is challenging primarily due to large deformations caused by the pathologies, leading to missing correspondences between scans. However, the registration task is …

Registration of Pathological Images

This paper proposes an approach to improve atlas-to-image registration accuracy with large pathologies. Instead of directly registering an atlas to a pathological image, the method learns a mapping from the pathological image to a quasi-normal image, …

Hierarchical task-driven feature learning for tumor histology

Through learning small and large-scale image features, we can capture the local and architectural structure of tumor tissue from histology images. This is done by learning a hierarchy of dictionaries using sparse coding, where each level captures …

Low-Rank to the Rescue - Atlas-Based Analyses in the Presence of Pathologies

Low-rank image decomposition has the potential to address a broad range of challenges that routinely occur in clinical practice. Its novelty and utility in the context of atlas-based analysis stems from its ability to handle images containing large …

PORTR: Pre-Operative and Post-Recurrence Brain Tumor Registration

We propose a new method for deformable registration of pre-operative and post-recurrence brain MR scans of glioma patients. Performing this type of intra-subject registration is challenging as tumor, resection, recurrence, and edema cause large …

Image and Statistical Analysis of Melanocytic Histology

Aims: We apply digital image analysis techniques to study selected types of melanocytic lesions. Methods and Results: We use advanced digital image analysis to compare melanocytic lesions. All comparisons were statistically significant (p < …