We previously developed an automatic catheter reconstruction model (CorneliUS) that achieves approximately 93% needle detection efficiency in post‑implant 3D ultrasound images for prostate HDR brachytherapy. The remaining undetected (AI‑missed) needles are ty...
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Mathieu Goulet, PhD
CISSS de Chaudière-Appalaches, département de radio-oncologie
Enhancing HDR Prostate Brachytherapy Deep Learning Needle Reconstruction with Live Ultrasound-Assisted Instance Detection
Poster Program · Therapy Physics
Implementation and Analysis of Deep Learning Needle Reconstruction Tool (CorneliUS) for US-Guided HDR Prostate Brachytherapy
To validate and assess the performance of an AI-assisted tool, CorneliUS, for needle reconstruction in high dose rate (HDR) ultrasound-guided prostate brachytherapy in an independent clinical setting.
Poster Program · Therapy Physics
Teamwork Makes the AI Work: Multi-Institutions Lung SBRT GTV Autosegmentation Using Federated Learning
Developing robust AI models for radiotherapy requires large, diverse datasets, which are difficult to share between institutions due to patient confidentiality, IT restrictions, and limited local machine learning expertise. Federated learning offers a solutio...
Poster Program · Therapy Physics