150 citations · 165 across the 9 of their papers we have counts for
5 papers · 1 filter
Compassionately Conservative Balanced Cuts for Image Segmentation
Nathan D. Cahill, Tyler L. Hayes, Renee T. Meinhold +1
The Normalized Cut (NCut) objective function, widely used in data clustering and image segmentation, quantifies the cost of graph partitioning in a way that biases clusters or segm…
Robust Spatial Filtering with Graph Convolutional Neural Networks
Felipe Petroski Such, Shagan Sah, Miguel Dominguez +5
Convolutional Neural Networks (CNNs) have recently led to incredible breakthroughs on a variety of pattern recognition problems. Banks of finite impulse response filters are learne…
Efficiently Computing Piecewise Flat Embeddings for Data Clustering and Image Segmentation
Renee T. Meinhold, Tyler L. Hayes, Nathan D. Cahill
Image segmentation is a popular area of research in computer vision that has many applications in automated image processing. A recent technique called piecewise flat embeddings (P…
Multiple-View Spectral Clustering for Group-wise Functional Community Detection
Nathan D. Cahill, Harmeet Singh, Chao Zhang +6
Functional connectivity analysis yields powerful insights into our understanding of the human brain. Group-wise functional community detection aims to partition the brain into clus…
Integrating Atlas and Graph Cut Methods for LV Segmentation from Cardiac Cine MRI
Shusil Dangi, Nathan Cahill, Cristian A. Linte
Magnetic Resonance Imaging (MRI) has evolved as a clinical standard-of-care imaging modality for cardiac morphology, function assessment, and guidance of cardiac interventions. All…