6 citations · 44 across the 67 of their papers we have counts for
14 papers · 1 filter
Morphological Decoupling-Based Skeletal Classification for Clinical Assessment of Malocclusion
Zhichun Jin, Zhicheng He, Hao Xu +4
Malocclusion skeletal grading is a fundamental task in orthodontics, critical for diagnosis and treatment planning. Traditionally, cone-beam computed tomography (CBCT) is used for…
DaX: Learning General Pathology Representations Across Scales
Bokai Zhao, Yiyang Zhang, Long Bai +3
Computational pathology requires visual representations that transfer across diverse clinical endpoints and remain robust to variation in magnification, staining, scanner type, sli…
EndoIR: Degradation-Agnostic All-in-One Endoscopic Image Restoration via Noise-Aware Routing Diffusion
Tong Chen, Xinyu Ma, Long Bai +3
Endoscopic images often suffer from diverse and co-occurring degradations such as low lighting, smoke, and bleeding, which obscure critical clinical details. Existing restoration m…
SurgTPGS: Semantic 3D Surgical Scene Understanding with Text Promptable Gaussian Splatting
Yiming Huang, Long Bai, Beilei Cui +6
In contemporary surgical research and practice, accurately comprehending 3D surgical scenes with text-promptable capabilities is particularly crucial for surgical planning and real…
Transferring Knowledge from High-Quality to Low-Quality MRI for Adult Glioma Diagnosis
Yanguang Zhao, Long Bai, Zhaoxi Zhang +3
Glioma, a common and deadly brain tumor, requires early diagnosis for improved prognosis. However, low-quality Magnetic Resonance Imaging (MRI) technology in Sub-Saharan Africa (SS…
EndoUIC: Promptable Diffusion Transformer for Unified Illumination Correction in Capsule Endoscopy
Long Bai, Tong Chen, Qiaozhi Tan +10
Wireless Capsule Endoscopy (WCE) is highly valued for its non-invasive and painless approach, though its effectiveness is compromised by uneven illumination from hardware constrain…
LighTDiff: Surgical Endoscopic Image Low-Light Enhancement with T-Diffusion
Tong Chen, Qingcheng Lyu, Long Bai +5
Advances in endoscopy use in surgeries face challenges like inadequate lighting. Deep learning, notably the Denoising Diffusion Probabilistic Model (DDPM), holds promise for low-li…
EndoDAC: Efficient Adapting Foundation Model for Self-Supervised Depth Estimation from Any Endoscopic Camera
Beilei Cui, Mobarakol Islam, Long Bai +2
Depth estimation plays a crucial role in various tasks within endoscopic surgery, including navigation, surface reconstruction, and augmented reality visualization. Despite the sig…
Adapting SAM for Surgical Instrument Tracking and Segmentation in Endoscopic Submucosal Dissection Videos
Jieming Yu, Long Bai, Guankun Wang +4
The precise tracking and segmentation of surgical instruments have led to a remarkable enhancement in the efficiency of surgical procedures. However, the challenge lies in achievin…
Joint Sparse Representations and Coupled Dictionary Learning in Multi-Source Heterogeneous Image Pseudo-color Fusion
Long Bai, Shilong Yao, Kun Gao +5
Considering that Coupled Dictionary Learning (CDL) method can obtain a reasonable linear mathematical relationship between resource images, we propose a novel CDL-based Synthetic A…
Landmark Detection using Transformer Toward Robot-assisted Nasal Airway Intubation
Tianhang Liu, Hechen Li, Long Bai +4
Robot-assisted airway intubation application needs high accuracy in locating targets and organs. Two vital landmarks, nostrils and glottis, can be detected during the intubation to…
LLCaps: Learning to Illuminate Low-Light Capsule Endoscopy with Curved Wavelet Attention and Reverse Diffusion
Long Bai, Tong Chen, Yanan Wu +3
Wireless capsule endoscopy (WCE) is a painless and non-invasive diagnostic tool for gastrointestinal (GI) diseases. However, due to GI anatomical constraints and hardware manufactu…
Domain Adaptive Sim-to-Real Segmentation of Oropharyngeal Organs Towards Robot-assisted Intubation
Guankun Wang, Tian-Ao Ren, Jiewen Lai +2
Robotic-assisted tracheal intubation requires the robot to distinguish anatomical features like an experienced physician using deep-learning techniques. However, real datasets of o…
Two-stage Contextual Transformer-based Convolutional Neural Network for Airway Extraction from CT Images
Yanan Wu, Shuiqing Zhao, Shouliang Qi +8
Accurate airway extraction from computed tomography (CT) images is a critical step for planning navigation bronchoscopy and quantitative assessment of airway-related chronic obstru…