4 citations · 6 across the 5 of their papers we have counts for
7 papers · 1 filter
Universal Lymph Node Detection in Multiparametric MRI with Selective Augmentation
Tejas Sudharshan Mathai, Sungwon Lee, Thomas C. Shen +2
Robust localization of lymph nodes (LNs) in multiparametric MRI (mpMRI) is critical for the assessment of lymphadenopathy. Radiologists routinely measure the size of LN to distingu…
Universal Lymph Node Detection in T2 MRI using Neural Networks
Tejas Sudharshan Mathai, Sungwon Lee, Thomas C. Shen +2
Purpose: Identification of abdominal Lymph Nodes (LN) that are suspicious for metastasis in T2 Magnetic Resonance Imaging (MRI) scans is critical for staging of lymphoproliferative…
Lymph Node Detection in T2 MRI with Transformers
Tejas Sudharshan Mathai, Sungwon Lee, Daniel C. Elton +4
Identification of lymph nodes (LN) in T2 Magnetic Resonance Imaging (MRI) is an important step performed by radiologists during the assessment of lymphoproliferative diseases. The…
Unsupervised Domain Adaptation for Small Bowel Segmentation using Disentangled Representation
Seung Yeon Shin, Sungwon Lee, Ronald M. Summers
We present a novel unsupervised domain adaptation method for small bowel segmentation based on feature disentanglement. To make the domain adaptation more controllable, we disentan…
Deep Small Bowel Segmentation with Cylindrical Topological Constraints
Seung Yeon Shin, Sungwon Lee, Daniel C. Elton +2
We present a novel method for small bowel segmentation where a cylindrical topological constraint based on persistent homology is applied. To address the touching issue which could…
Cross-Domain Medical Image Translation by Shared Latent Gaussian Mixture Model
Yingying Zhu, Youbao Tang, Yuxing Tang +4
Current deep learning based segmentation models often generalize poorly between domains due to insufficient training data. In real-world clinical applications, cross-domain image a…