John J Volpi

Title: John J. Volpi and Deep-Learning CT Denoising.

Introduction

John J. Volpi is an inventor associated with Houston, Texas, and The Methodist Hospital. His work includes a patent describing a deep-learning approach to reducing noise in computed tomography (CT) images, with a focus on supporting clearer imaging for acute ischemic stroke assessment.

Latest Patents

Volpi is associated with 1 patent: “Method of CT Denoising Employing Deep Learning of Multiple Co-Registered Scans of the Same Person and Group Convolutional Neural Network Analyses.” The disclosed method uses deep learning to improve the signal-to-noise ratio in CT images. In reported evaluations, it reduced image noise more effectively than BM3D and improved signal-to-noise ratios in gray matter, white matter, and deep gray matter by 2.47×, 2.83×, and 2.64×, respectively. It also improved contrast-to-noise ratios in deep gray matter/white matter and gray matter/white matter by 2.30× and 2.16×, respectively. The denoised scans were reported to appear clearer while preserving anatomy, and the model was evaluated on 380 previously unseen head non-contrast CT cases.

Career Highlights

Volpi’s listed organizational affiliation is The Methodist Hospital. The patent’s application of deep learning to medical imaging reflects an effort to improve CT image quality while retaining anatomical detail relevant to clinical interpretation.

Collaborations

The provided information identifies Kelvin Wong and Stephen T. C. Wong as Volpi’s coworkers. Their names are associated here as workplace colleagues; the supplied details do not specify their roles in the patent.

Conclusion

John J. Volpi’s patent focuses on using deep learning to reduce noise in CT scans, with reported improvements in image quality that may support the assessment of acute ischemic stroke.