5 citations · 10 across the 8 of their papers we have counts for
8 papers
EndoStreamDepth: Temporally Consistent Monocular Depth Estimation for Endoscopic Video Streams
Hao Li, Daiwei Lu, Jiacheng Wang +2
This work presents EndoStreamDepth, a monocular depth estimation framework for endoscopic video streams. It provides accurate depth maps with sharp anatomical boundaries for each f…
Endo-SemiS: Towards Robust Semi-Supervised Image Segmentation for Endoscopic Video
Hao Li, Daiwei Lu, Xing Yao +2
In this paper, we present Endo-SemiS, a semi-supervised segmentation framework for providing reliable segmentation of endoscopic video frames with limited annotation. EndoSemiS use…
Monocular absolute depth estimation from endoscopy via domain-invariant feature learning and latent consistency
Hao Li, Daiwei Lu, Jesse d'Almeida +8
Monocular depth estimation (MDE) is a critical task to guide autonomous medical robots. However, obtaining absolute (metric) depth from an endoscopy camera in surgical scenes is di…
SynStitch: a Self-Supervised Learning Network for Ultrasound Image Stitching Using Synthetic Training Pairs and Indirect Supervision
Xing Yao, Runxuan Yu, Dewei Hu +10
Ultrasound (US) image stitching can expand the field-of-view (FOV) by combining multiple US images from varied probe positions. However, registering US images with only partially o…
AdaptDiff: Cross-Modality Domain Adaptation via Weak Conditional Semantic Diffusion for Retinal Vessel Segmentation
Dewei Hu, Hao Li, Han Liu +4
Deep learning has shown remarkable performance in medical image segmentation. However, despite its promise, deep learning has many challenges in practice due to its inability to ef…
False Negative/Positive Control for SAM on Noisy Medical Images
Xing Yao, Han Liu, Dewei Hu +9
The Segment Anything Model (SAM) is a recently developed all-range foundation model for image segmentation. It can use sparse manual prompts such as bounding boxes to generate pixe…
SSL^2: Self-Supervised Learning meets Semi-Supervised Learning: Multiple Sclerosis Segmentation in 7T-MRI from large-scale 3T-MRI
Jiacheng Wang, Hao Li, Han Liu +6
Automated segmentation of multiple sclerosis (MS) lesions from MRI scans is important to quantify disease progression. In recent years, convolutional neural networks (CNNs) have sh…
Segmentation of kidney stones in endoscopic video feeds
Zachary A Stoebner, Daiwei Lu, Seok Hee Hong +2
Image segmentation has been increasingly applied in medical settings as recent developments have skyrocketed the potential applications of deep learning. Urology, specifically, is…