32 citations · 45 across the 8 of their papers we have counts for
8 papers
SwinCross: Cross-modal Swin Transformer for Head-and-Neck Tumor Segmentation in PET/CT Images
Gary Y. Li, Junyu Chen, Se-In Jang +2
Radiotherapy (RT) combined with cetuximab is the standard treatment for patients with inoperable head and neck cancers. Segmentation of head and neck (H&N) tumors is a prerequisite…
Deterministic Online Classification: Non-iteratively Reweighted Recursive Least-Squares for Binary Class Rebalancing
Se-In Jang
Deterministic solutions are becoming more critical for interpretability. Weighted Least-Squares (WLS) has been widely used as a deterministic batch solution with a specific weight…
Investigation of Network Architecture for Multimodal Head-and-Neck Tumor Segmentation
Ye Li, Junyu Chen, Se-in Jang +2
Inspired by the recent success of Transformers for Natural Language Processing and vision Transformer for Computer Vision, many researchers in the medical imaging community have fl…
Spach Transformer: Spatial and Channel-wise Transformer Based on Local and Global Self-attentions for PET Image Denoising
Se-In Jang, Tinsu Pan, Ye Li +4
Position emission tomography (PET) is widely used in clinics and research due to its quantitative merits and high sensitivity, but suffers from low signal-to-noise ratio (SNR). Rec…
Explainable and Interpretable Diabetic Retinopathy Classification Based on Neural-Symbolic Learning
Se-In Jang, Michael J. A. Girard, Alexandre H. Thiery
In this paper, we propose an explainable and interpretable diabetic retinopathy (ExplainDR) classification model based on neural-symbolic learning. To gain explainability, a highle…
A Noise-level-aware Framework for PET Image Denoising
Ye Li, Jianan Cui, Junyu Chen +7
In PET, the amount of relative (signal-dependent) noise present in different body regions can be significantly different and is inherently related to the number of counts present i…
Online Passive-Aggressive Total-Error-Rate Minimization
Se-In Jang
We provide a new online learning algorithm which utilizes online passive-aggressive learning (PA) and total-error-rate minimization (TER) for binary classification. The PA learning…
An LBP-HOG Descriptor Based on Matrix Projection For Mammogram Classification
Zainab Alhakeem, Se-In Jang
In image based feature descriptor design, local information from image patches are extracted using iterative scanning operations which cause high computational costs. In order to a…