Search Results for author:
Found 5 papers, 1 papers with code
Colonoscopy 3D Video Dataset with Paired Depth from 2D-3D Registration
In this work, we present a Colonoscopy 3D Video Dataset (C3VD) acquired with a high definition clinical colonoscope and high-fidelity colon models for benchmarking computer vision methods in colonoscopy.
GAN Inversion for Data Augmentation to Improve Colonoscopy Lesion Classification
This study demonstrates that synthetic colonoscopy images generated by Generative Adversarial Network (GAN) inversion can be used as training data to improve the lesion classification performance of deep learning models.
Improving colonoscopy lesion classification using semi-supervised deep learning
While data-driven approaches excel at many image analysis tasks, the performance of these approaches is often limited by a shortage of annotated data available for training.
SLAM Endoscopy enhanced by adversarial depth prediction
Medical endoscopy remains a challenging application for simultaneous localization and mapping (SLAM) due to the sparsity of image features and size constraints that prevent direct depth-sensing.
DeepLSR: a deep learning approach for laser speckle reduction
In images of gastrointestinal tissues, DeepLSR reduces laser speckle noise by 6. 4 dB, compared to a 2. 9 dB reduction from optimized non-local means processing, a 3. 0 dB reduction from BM3D, and a 3. 7 dB reduction from an optical speckle reducer utilizing an oscillating diffuser.
