Tag: #JOSHUA

Abstract: Feature engineering often plays a vital role in the fields of computer vision and machine learning. A few common examples of engineered features include histogram of oriented gradients (HOG) (Dalal and Triggs, 2005), local binary patterns (LBP) (Ojala et al., 1994), and edge histogram descriptors (EHD) (Frigui and Gader, 2008). Features such as pixel […]

Congratulations to our labmates and collaborators: Joshua K. Peeples, Julie F. Jameson, Nisha M. Kotta, Jonathan M. Grasman, Whitney L. Stoppel and Alina Zare! Their paper, “Jointly Optimized Spatial Histogram UNET Architecture (JOSHUA) for Adipose Tissue Segmentation”, was recently accepted to BME Frontiers Special Issue: AI for Advanced Biomedical Applications, 2022. In the paper, the […]

Abstract: Objective: We quantify adipose tissue deposition at surgical sites as a function of biomaterial implantation. Impact Statement: To our knowledge, this study is the first investigation to apply convolutional neural network (CNN) models to identify and segment adipose tissue in histological images from silk fibroin biomaterial implants. Introduction: When designing biomaterials for the treatment […]