14 citations · 86 across the 23 of their papers we have counts for
9 papers · 1 filter
A Continual Learning-driven Model for Accurate and Generalizable Segmentation of Clinically Comprehensive and Fine-grained Whole-body Anatomies in CT
Dazhou Guo, Zhanghexuan Ji, Yanzhou Su +31
Precision medicine in the quantitative management of chronic diseases and oncology would be greatly improved if the Computed Tomography (CT) scan of any patient could be segmented,…
Accurate Airway Tree Segmentation in CT Scans via Anatomy-aware Multi-class Segmentation and Topology-guided Iterative Learning
Puyang Wang, Dazhou Guo, Dandan Zheng +8
Intrathoracic airway segmentation in computed tomography (CT) is a prerequisite for various respiratory disease analyses such as chronic obstructive pulmonary disease (COPD), asthm…
Multi-site, Multi-domain Airway Tree Modeling (ATM'22): A Public Benchmark for Pulmonary Airway Segmentation
Minghui Zhang, Yangqian Wu, Hanxiao Zhang +33
Open international challenges are becoming the de facto standard for assessing computer vision and image analysis algorithms. In recent years, new methods have extended the reach o…
Comprehensive and Clinically Accurate Head and Neck Organs at Risk Delineation via Stratified Deep Learning: A Large-scale Multi-Institutional Study
Dazhou Guo, Jia Ge, Xianghua Ye +22
Accurate organ at risk (OAR) segmentation is critical to reduce the radiotherapy post-treatment complications. Consensus guidelines recommend a set of more than 40 OARs in the head…
SAME: Deformable Image Registration based on Self-supervised Anatomical Embeddings
Fengze Liu, Ke Yan, Adam Harrison +8
In this work, we introduce a fast and accurate method for unsupervised 3D medical image registration. This work is built on top of a recent algorithm SAM, which is capable of compu…
DeepStationing: Thoracic Lymph Node Station Parsing in CT Scans using Anatomical Context Encoding and Key Organ Auto-Search
Dazhou Guo, Xianghua Ye, Jia Ge +9
Lymph node station (LNS) delineation from computed tomography (CT) scans is an indispensable step in radiation oncology workflow. High inter-user variabilities across oncologists a…
Lymph Node Gross Tumor Volume Detection and Segmentation via Distance-based Gating using 3D CT/PET Imaging in Radiotherapy
Zhuotun Zhu, Dakai Jin, Ke Yan +7
Finding, identifying and segmenting suspicious cancer metastasized lymph nodes from 3D multi-modality imaging is a clinical task of paramount importance. In radiotherapy, they are…
Deep Esophageal Clinical Target Volume Delineation using Encoded 3D Spatial Context of Tumors, Lymph Nodes, and Organs At Risk
Dakai Jin, Dazhou Guo, Tsung-Ying Ho +4
Clinical target volume (CTV) delineation from radiotherapy computed tomography (RTCT) images is used to define the treatment areas containing the gross tumor volume (GTV) and/or su…
Accurate Esophageal Gross Tumor Volume Segmentation in PET/CT using Two-Stream Chained 3D Deep Network Fusion
Dakai Jin, Dazhou Guo, Tsung-Ying Ho +4
Gross tumor volume (GTV) segmentation is a critical step in esophageal cancer radiotherapy treatment planning. Inconsistencies across oncologists and prohibitive labor costs motiva…