Fugen Zhou

Dual-domain dual-branch residual-learning network for fast noisy sparse-view ultra-low-dose CT reconstruction

Jiabing Xiang, Yi Yang, Yanxin Wang, Fugen Zhou et autres

Abstract Objective. Ultra-low-dose CT (ULDCT) can be achieved by reducing the tube current and employing sparse-view projections, thereby improving patient safety by lowering radiation exposure. However, this strategy inevitably introduces severe aliasing artifacts and increased noise, leading to substantial degradation of image …

cn (code pays fourni par la source)

Multi-class segmentation of aortic branches and zones in computed tomography angiography: The AortaSeg24 challenge

Muhammad Ali Imran, Jonathan R. Krebs, Vishal Balaji Sivaraman, Teng Zhang et autres

us, cn, de, kr, at, ru, ch, pl, gb, dk (code pays fourni par la source)

Multi-needle Localization for Pelvic Seed Implant Brachytherapy based on Tip-handle Detection and Matching

Zhuo Xiao, Fugen Zhou, Jing Jing Wang, Chun He et autres

Accurate multi-needle localization in intraoperative CT images is crucial for optimizing seed placement in pelvic seed implant brachytherapy. However, this task is challenging due to poor image contrast and needle adhesion. This paper presents a novel approach that reframes needle localization as …

cn, us (code pays fourni par la source)

MAA-Net: A Multi-attention Aggregation Network for Segmentation of Key Structures in Microvascular Decompression

Jinghua Yue, Fugen Zhou, Qinglong Yao, Bo Liu et autres

cn (code pays fourni par la source)

Advancing Depth Anything Model for Unsupervised Monocular Depth Estimation in Endoscopy

Bojian Li, Bo Hong Liu, Jinghua Yue, Fugen Zhou

Depth estimation is a cornerstone of 3D reconstruction and plays a vital role in minimally invasive endoscopic surgeries. However, most current depth estimation networks rely on traditional convolutional neural networks, which are limited in their ability to capture global information. Foundation models …

cn (code pays fourni par la source)

An Iterative LLM Framework for SIBT utilizing RAG-based Adaptive Weight Optimization

Zhuo Xiao, Qi Yao, Jingjing Wang, Fugen Zhou et autres

Seed implant brachytherapy (SIBT) is an effective cancer treatment modality; however, clinical planning often relies on manual adjustment of objective function weights, leading to inefficiencies and suboptimal results. This study proposes an adaptive weight optimization framework for SIBT planning, driven by large …

cn, us (code pays fourni par la source)

Semantic-CD: Remote Sensing Image Semantic Change Detection Towards Open-Vocabulary Setting

Yongshuo Zhu, Lu Li, Kexin Chen, Chenyang Liu et autres

Remote sensing image semantic change detection is a method used to analyze remote sensing images, aiming to identify areas of change as well as categorize these changes within images of the same location taken at different times. Traditional change detection methods often …

cn (code pays fourni par la source)

Multiphase difference enhanced fusion for tumor and pancreas segmentation

Chun He, Fugen Zhou, Бо Лю, Jiaping Li et autres

Multi-phase contrast-enhanced computed tomography (CECT) has been shown to effectively refine the segmentation accuracy for both tumors and organs. Nevertheless, enhancing the segmentation accuracy of the pancreas and pancreatic tumors using multi-phase CECT remains a challenge, which is crucial for subsequent clinical …

cn (code pays fourni par la source)

Deep learning-based segmentation for high-dose-rate brachytherapy in cervical cancer using 3D Prompt-ResUNet

Xian Xue, Lining Sun, Dazhu Liang, Jingyang Zhu et autres

Abstract Objective. To develop and evaluate a 3D Prompt-ResUNet module that utilized the prompt-based model combined with 3D nnUNet for rapid and consistent autosegmentation of high-risk clinical target volume (HRCTV) and organ at risk (OAR) in high-dose-rate brachytherapy for cervical cancer patients. …

cn, gb, ph (code pays fourni par la source)

Advancing Depth Anything Model for Unsupervised Monocular Depth Estimation in Endoscopy

Bojian Li, Bo Liu, Jinghua Yue, Fugen Zhou

Depth estimation is a cornerstone of 3D reconstruction and plays a vital role in minimally invasive endoscopic surgeries. However, most current depth estimation networks rely on traditional convolutional neural networks, which are limited in their ability to capture global information. Foundation models …

A shape-supervised feature fusion U-Net for tubular structure segmentation

Jinghua Yue, Shuo Jin, Siyuan Wang, Jianping Zeng et autres

cn (code pays fourni par la source)

An end‐to‐end deep convolutional neural network‐based dose engine for parotid gland cancer seed implant brachytherapy

Tianyu Xiong, Jing Yan Cai, Fugen Zhou, Bo Hong Liu et autres

Abstract Background Seed implant brachytherapy (SIBT) is a promising treatment modality for parotid gland cancers (PGCs). However, the current clinical standard dose calculation method based on the American Association of Physicists in Medicine (AAPM) Task Group 43 (TG‐43) Report oversimplifies patient anatomy …

hk, cn, us (code pays fourni par la source)