Publications by authors named "Ruizhi Zuo"
High-resolution 4D-OCT fish-eye imaging using 3D-UNet with multi-level residue decoder.
Biomed Opt Express
September 2024
Article Synopsis
- Optical coherence tomography (OCT) is a method for creating detailed 3D images of biological tissues, but it can be affected by motion artifacts from slow frame rates and movement.
- A new real-time 4D-OCT system uses a deep learning algorithm to produce high-quality volumetric images quickly by collecting unmatched images and enhancing them with a convolutional neural network (CNN).
- The study compares different deep learning network architectures to improve the image reconstruction process, ultimately achieving precise tissue structure retrieval and real-time imaging at rates over 10 Hz with minimal error.
Anastomosis is a common and critical part of reconstructive procedures within gastrointestinal, urologic, and gynecologic surgery. The use of autonomous surgical robots such as the smart tissue autonomous robot (STAR) system demonstrates an improved efficiency and consistency of the laparoscopic small bowel anastomosis over the current da Vinci surgical system. However, the STAR workflow requires auxiliary manual monitoring during the suturing procedure to avoid missed or wrong stitches.
View Article and Find Full Text PDFSignificance: Optical coherence tomography (OCT) allows high-resolution volumetric three-dimensional (3D) imaging of biological tissues in vivo. However, 3D-image acquisition can be time-consuming and often suffers from motion artifacts due to involuntary and physiological movements of the tissue, limiting the reproducibility of quantitative measurements.
Aim: To achieve real-time 3D motion compensation for corneal tissue with high accuracy.