A5077575641- Advanced Radiotherapy Techniques
- Lung Cancer Diagnosis and Treatment
- Radiomics and Machine Learning in Medical Imaging
- Medical Imaging Techniques and Applications
- Radiation Therapy and Dosimetry
- Head and Neck Cancer Studies
- Glioma Diagnosis and Treatment
- Esophageal Cancer Research and Treatment
- Medical Image Segmentation Techniques
- Artificial Intelligence in Healthcare and Education
- Generative Adversarial Networks and Image Synthesis
- Systemic Sclerosis and Related Diseases
- Medical Imaging and Analysis
- Advanced Image Processing Techniques
- Nuclear Physics and Applications
- Radiation Dose and Imaging
- Pancreatic and Hepatic Oncology Research
- Mechanical Failure Analysis and Simulation
- Colorectal Cancer Screening and Detection
- Occupational Health and Safety Research
- Advanced MRI Techniques and Applications
- Clinical practice guidelines implementation
- Cancer Immunotherapy and Biomarkers
- Quality and Safety in Healthcare
- Brain Metastases and Treatment
Emory University
2023-2025
Emory Healthcare
2022-2024
Abstract Purpose Deep learning‐based segmentation of organs‐at‐risk (OAR) is emerging to become mainstream in clinical practice because the superior performance over atlas and model‐based autocontouring methods. While several commercial deep autosegmentation solutions are now available, implementation these tools still at such a primitive stage that acceptance criteria underdeveloped due lack knowledge about systems’ tendencies failure modes. As starting point iterative process...
Abstract Purpose To investigate bolus design and VMAT optimization settings for total scalp irradiation. Methods Three silicone designs (flat, hat, custom) from .decimal were evaluated adherence to five anthropomorphic head phantoms. Flat was cut a sheet. Generic hat resembles an elongated swim cap while custom is manufactured by injecting into 3D printed mold. Bolus placement time recorded. Air gaps between quantified on CT images. The dosimetric effect of air target coverage in treatment...
Abstract In this work, we demonstrate a method for rapid synthesis of high‐quality CT images from unpaired, low‐quality CBCT images, permitting CBCT‐based adaptive radiotherapy. We adapt contrastive unpaired translation (CUT) to be used with medical and evaluate the results on an institutional pelvic dataset. compare against cycleGAN using mean absolute error, structural similarity index, root squared Frèchet Inception Distance show that CUT significantly outperforms while requiring less...
This study evaluated the feasibility of using artificial intelligence (AI) segmentation software for volume-modulated arc therapy (VMAT) prostate planning in conjunction with knowledge-based to facilitate a fully automated workflow. Two commercially available AI programs, Radformation AutoContour (Radformation, New York, NY) and Siemens AI-Rad Companion (Siemens Healthineers, Malvern, PA) were used auto-segment rectum, bladder, femoral heads, bowel bag on 30 retrospective clinical cases (10...
The implementation of knowledge-based planning (KBP) continues to grow in radiotherapy clinics. KBP guides radiation treatment design by generating clinically acceptable plans a timely and resource-efficient manner. role multiple models tailored for variations within disease site remains undefined part because the substantial effort number training cases required create high-quality model. In this study, our aim was explore whether site-specific lead meaningful differences plan quality...