451 citations · 731 across the 3 of their papers we have counts for
3 papers
Atlas Based Segmentations via Semi-Supervised Diffeomorphic Registrations
Charles Huang, Masoud Badiei, Hyunseok Seo +5
Purpose: Segmentation of organs-at-risk (OARs) is a bottleneck in current radiation oncology pipelines and is often time consuming and labor intensive. In this paper, we propose an…
Machine Learning Techniques for Biomedical Image Segmentation: An Overview of Technical Aspects and Introduction to State-of-Art Applications
Hyunseok Seo, Masoud Badiei Khuzani, Varun Vasudevan +5
In recent years, significant progress has been made in developing more accurate and efficient machine learning algorithms for segmentation of medical and natural images. In this re…
Modified U-Net (mU-Net) with Incorporation of Object-Dependent High Level Features for Improved Liver and Liver-Tumor Segmentation in CT Images
Hyunseok Seo, Charles Huang, Maxime Bassenne +2
Segmentation of livers and liver tumors is one of the most important steps in radiation therapy of hepatocellular carcinoma. The segmentation task is often done manually, making it…