1 citations · 3 across the 13 of their papers we have counts for
13 papers
LISynSeg: Data-Centric Label-to-Image Synthesis for Cross-Modality Whole-Heart Segmentation
Jiacheng Wang, Ivana Isgum, Ipek Oguz
Whole-heart segmentation (WHS) in computed tomography (CT) and magnetic resonance imaging (MRI) is affected by acquisition shifts and heterogeneous cardiac annotations. Existing WH…
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…
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…
PRISM Lite: A lightweight model for interactive 3D placenta segmentation in ultrasound
Hao Li, Baris Oguz, Gabriel Arenas +6
Placenta volume measured from 3D ultrasound (3DUS) images is an important tool for tracking the growth trajectory and is associated with pregnancy outcomes. Manual segmentation is…
Retinal IPA: Iterative KeyPoints Alignment for Multimodal Retinal Imaging
Jiacheng Wang, Hao Li, Dewei Hu +4
We propose a novel framework for retinal feature point alignment, designed for learning cross-modality features to enhance matching and registration across multi-modality retinal i…
Interactive Segmentation Model for Placenta Segmentation from 3D Ultrasound images
Hao Li, Baris Oguz, Gabriel Arenas +6
Placenta volume measurement from 3D ultrasound images is critical for predicting pregnancy outcomes, and manual annotation is the gold standard. However, such manual annotation is…
Predicting fluorescent labels in label-free microscopy images with pix2pix and adaptive loss in Light My Cells challenge
Han Liu, Hao Li, Jiacheng Wang +3
Fluorescence labeling is the standard approach to reveal cellular structures and other subcellular constituents for microscopy images. However, this invasive procedure may perturb…
PRISM: A Promptable and Robust Interactive Segmentation Model with Visual Prompts
Hao Li, Han Liu, Dewei Hu +2
In this paper, we present PRISM, a Promptable and Robust Interactive Segmentation Model, aiming for precise segmentation of 3D medical images. PRISM accepts various visual inputs,…
Assessing Test-time Variability for Interactive 3D Medical Image Segmentation with Diverse Point Prompts
Hao Li, Han Liu, Dewei Hu +2
Interactive segmentation model leverages prompts from users to produce robust segmentation. This advancement is facilitated by prompt engineering, where interactive prompts serve a…
Promise:Prompt-driven 3D Medical Image Segmentation Using Pretrained Image Foundation Models
Hao Li, Han Liu, Dewei Hu +2
To address prevalent issues in medical imaging, such as data acquisition challenges and label availability, transfer learning from natural to medical image domains serves as a viab…
Novel OCT mosaicking pipeline with Feature- and Pixel-based registration
Jiacheng Wang, Hao Li, Dewei Hu +2
High-resolution Optical Coherence Tomography (OCT) images are crucial for ophthalmology studies but are limited by their relatively narrow field of view (FoV). Image mosaicking is…
MAP: Domain Generalization via Meta-Learning on Anatomy-Consistent Pseudo-Modalities
Dewei Hu, Hao Li, Han Liu +3
Deep models suffer from limited generalization capability to unseen domains, which has severely hindered their clinical applicability. Specifically for the retinal vessel segmentat…