Deep Learning Segmentation for Accurate GTV and OAR Segmentation in MR-Guided Adaptive Radiotherapy for Pancreatic Cancer Patients
AAPM 2023, ASTRO 2023
Poster
Novel Functional Radiomics for Predicting Cardiotoxicity in Lung Cancer Radiotherapy using Cardiac FDG-PET Uptake
Our paper “Novel Functional Radiomics for Prediction of Cardiac Positron Emission Tomography Avidity in Lung Cancer Radiotherapy” has been published in JCO CCI. This research work delves into an innovative approach to predict clinical cardiac assessment using functional imaging. Note: This post summarizes broader functional cardiac PET radiomics work. Only one related presentation below is specifically a delta-radiomics analysis. Abstract: Traditional methods for evaluating cardiotoxicity primarily focus on radiation doses to the heart. However, functional imaging offers the potential to enhance early prediction of cardiotoxicity in lung cancer patients undergoing radiotherapy. In this context, Fluorine-18 (18F) fluorodeoxyglucose (FDG)-positron emission tomography (PET)/computed tomography (CT) imaging plays a crucial role. This study aims to develop a radiomics model that predicts clinical cardiac assessment using 18F-FDG PET/CT scans before thoracic radiation therapy. ...
Automatic motion tracking system for analysis of insect behavior
Darrin Gladman, Jehu Osegbe, Wookjin Choi*, and Joon Suk Lee “Automatic motion tracking system for analysis of insect behavior”, Proc. SPIE 11510, Applications of Digital Image Processing XLIII, 115102W (21 August 2020); https://doi.org/10.1117/12.2568804 *Corresponding author Abstract We present a multi-object tracking system to track small insects such as ants and bees. Motion-based object tracking recognizes the movements of objects in videos using information extracted from the given video frames. We applied several computer vision techniques, such as blob detection and appearance matching, to track ants. Moreover, we discussed different object detection methodologies and investigated the various challenges of object detection, such as illumination variations and blob merge/split. The proposed system effectively tracked multiple objects in various environments. ...
Assessing the Dosimetric Links between Organ-At-Risk Delineation Variability and Treatment Planning Variability
The 2020 Joint AAPM | COMP Virtual Meeting https://w3.aapm.org/meetings/2020AM/programInfo/programAbs.php?sid=8490&aid=52949
Robust Normal Lung CT Texture Features for the Prediction of Radiation-Induced Lung Disease
2017 ASTRO annual meeting http://www.redjournal.org/article/S0360-3016(17)31540-7/fulltext
Individually Optimized Contrast-Enhanced 4D-CT for Radiotherapy Simulation in Pancreatic Adenocarcinoma
2016 ASTRO annual meeting This poster has been selected for the ARRO poster walk (6 out of 250 physics posters). http://onlinelibrary.wiley.com/doi/10.1118/1.4963213/full
Identification of Robust Normal Lung CT Texture Features for the Prediction of Radiation-Induced Lung Disease
2016 AAPM annual meeting http://onlinelibrary.wiley.com/doi/10.1118/1.4955803/abstract
Quantitative Image Feature Analysis of Multiphase Liver CT for Hepatocellular Carcinoma (HCC) in Radiation Therapy
2015 AAPM annual meeting
Image quality assessment of contrast-enhanced 4D-CT for pancreatic adenocarcinoma in radiotherapy simulation
2015 AAPM annual meeting
Computer-aided Detection of Pulmonary Nodules using Genetic Programming
2010 IEEE ICIP