Dazhou Guo

Senior Algorithm Engineer
@ Alibaba DAMO Academy
Email: guo2004131 [at] gmail [dot] com
CV | GoogleScholar | LinkedIn

Brief Bio

Since 2022, I have been working at Alibaba DAMO Academy as a senior algorithm engineer. I am working closely with amazing talented colleagues and clinical physicians/oncologists. My projects are related to radiotherapy target volume segmentation, organ segmentation, treatment response, and prognostic analysis. Before that, I was a senior research scientist at PAII Inc. I am supervised and mentored by Dr. Le Lu .

Updates

[07/2024] One abstract is accepted by RSNA 2024. Congrats to Hongxi and Hexuan!

[06/2024] One paper on airway segmentation is accepted by IEEE TMI 2024. Congrats to Puyang!

[06/2024] Two papers are accepted by MICCAI 2024. Congrats to Hongxi, Hexuan, Haoshen, Yirui!

[07/2023] One paper is accepted by ICCV 2023. Congrats to Hexuan!

[07/2023] One abstracts are accepted by RSNA 2023.

[06/2023] One paper is accepted by IEEE TMI 2023.

[05/2023] One abstract are accepted by ASTRO 2023.

[12/2022] One invaited reviewing paper is accepted by Journal of the National Cancer Center.

[10/2022] One paper is accepted by Nature Communications.

[07/2022] Three abstracts are accepted by RSNA 2022. (All oral presentations)

[06/2022] Three abstracts are accepted by ASTRO 2022.

[06/2022] One lymph node segmentation paper is accepted by MICCAI 2022.

[04/2022] One paper titled "SAM "on self-supervised anatomical embeddings is accepted by IEEE TMI. (Congrats to Ke!)

[10/2021] One paper on multi-institutional validation of esophageal GTV segmentation is accepted by Frontiers in Oncology.

[06/2021] Two papers on lymph node station parsing and unsupervised deformable registration are accepted by MICCAI 2021.

[05/2021] Three abstracts are accepted by American Society for Radiation Oncology (ASTRO) 2021.

[05/2021] One co-author paper on COVID-19 risk factor study is accepted by Frontiers in Radiology 2021.

[02/2021] Guest Editor for a special issue "Machine Learning for Quantitative Neuroimaging Analysis" in Frontiers in Neuroscience (IF:3.7, h5-index 80). Welcome to contribute!

[09/2020] One paper titled "DeepTarget" is accepted by Medical Image Analysis. (Special Issue of MICCAI-2019 Best Papers)

[11/2020] One paper on esophageal GTV & CTV segmentation is accepted by Medical Image Analysis, Selected Papers Special Issue.

[09/2020] Two abstracts are accepted by RSNA (both oral presentations).

[05/2020] Two papers on the lymph node delineation are accepted to MICCAI 2020 (both early accepts).

[03/2020] One paper on comprehensive head & neck OAR segmentation is accepted by CVPR 2020.

[08/2019] One papers on degraded image semantic segmentation is accepted by IEEE Trans on Image Processing.

[08/2019] One papers on co-saliency detection is accepted by Neurocomputing.

[04/2019] One papers on weakly supervised object detection is accepted by Neurocomputing.

[04/2019] Two papers on GTV & CTV segmentation are accepted by MICCAI 2019 (both early accepts, one oral presentation).

Publications

2024

[ECCV] Effective Lymph Nodes Detection in CT Scans Using Location Debiased Query Selection and Contrastive Query Representation in Transformer.Qinji Yu*, Yirui Wang*, Ke Yan, Haoshen Li, Dazhou Guo, Li Zhang, Le Lu, Na Shen, Qifeng Wang, Xiaowei Ding, Xianghua Ye, Dakai Jin.

[IEE TMI] Accurate Airway Tree Segmentation in CT Scans via Anatomy-aware Multi-class Segmentation and Topology-guided Iterative Learning.Puyang Wang, Dazhou Guo, Dandan Zheng, Minghui Zhang, Haogang Yu, Xin Sun, Jia Ge, Yun Gu, Le Lu, Xianghua Ye, Dakai Jin.

[MICCAI] Semi-supervised Lymph Node Metastasis Classification with Pathology-guided Label Sharpening and Two-streamed Multi-scale Fusion.Haoshen Li, Yirui Wang, Jie Zhu, Dazhou Guo, Qinji Yu, Ke Yan, Le Lu, Xianghua Ye, Li Zhang, Qifeng Wang, Dakai Jin.

[MICCAI] Low-Rank Continual Pyramid Vision Transformer: Incrementally Segment Whole-Body Organs in CT with Light-Weighted Adaptation.Vince Zhu, Zhanghexuan Ji, Dazhou Guo, Puyang Wang, Yingda Xia, Le Lu, Xianghua Ye, Wei Zhu, Dakai Jin.

2023

[ICCV] Continual segment: Towards a single, unified and non-forgetting continual segmentation model of 143 whole-body organs in ct scans. Zhanghexuan Ji*, Dazhou Guo*, Puyang Wang, Ke Yan, Le Lu, Minfeng Xu, Jingren Zhou, Qifeng Wang, Jia Ge, Mingchen Gao, Xianghua Ye, Dakai Jin.

[TMI] LViT: Language meets Vision Transformer in Medical Image Segmentation. Zihan Li, Yunxiang Li, Qingde Li, Puyang Wang, Dazhou Guo, Le Lu, Dakai Jin, You Zhang, Qingqi Hong.

[MICCAI MMM] Anatomy-Aware Lymph Node Detection in Chest CT using Implicit Station Stratification. Ke Yan, Dakai Jin, Dazhou Guo, Minfeng Xu, Na Shen, Xian-Sheng Hua, Xianghua Ye, Le Lu.

2022

[Nature Communications] Comprehensive and Clinically Accurate Head and Neck Cancer Organs-at-Risk Delineation on a Multi-Institutional Study. Xianghua Ye*, Dazhou Guo*, Jia Ge*, Senxiang Yan, Yi Xin, Yuchen Song, Yongheng Yan, Bing-shen Huang, Tsung-Min Hung, Zhuotun Zhu, Ling Peng, Yanping Ren, Rui Liu, Gong Zhang, Mengyuan Mao, Xiaohua Chen, Zhongjie Lu, Wenxiang Li, Yuzhen Chen, Lingyun Huang, Jing Xiao, Adam Harrison, Le Lu, Chien-Yu Lin^, Dakai Jin^, Tsung-Ying Ho^.

[JNCC] Towards Automated Organs at Risk and Target Volumes Contouring: Defining Precision Radiation Therapy in the Modern Era. Dakai Jin, Dazhou Guo, Jia Ge, Xianghua Ye, Le Lu. (Invited reviewing article)

[MICCAI] Thoracic Lymph Node Segmentation in CT imaging via Lymph Node Station Stratification and Size Encoding. Dazhou Guo, Jia Ge, Ke Yan, Puyang Wang, Zhuotun Zhu, Dandan Zheng, Xiansheng Hua, Le Lu, Tsung-Ying Ho, Xianghua Ye, Dakai Jin.

[IEE TMI] SAM: Self-supervised Learning of Pixel-wise Anatomical Embeddings in Radiological Images. Ke Yan, Jinzheng Cai, Dakai Jin, Shun Miao, Adam P Harrison, Dazhou Guo, Youbao Tang, Jing Xiao, Jingjing Lu, Le Lu.[pdf]

2021

[Frontiers in Oncology] Multi-Institutional Validation of Two-Streamed Deep Learning Method for Automated Delineation of Esophageal Gross Tumor Volume Using Planning CT and FDG-PET/CT. Xianghua Ye*, Dazhou Guo*, Chen-kan Tseng, Jia Ge, Tsung-Min Hung, Ping-Ching Pai, Yanping Ren, Lu Zheng, Xinli Zhu, Ling Peng, Ying Chen, Xiaohua Chen, Chen-Yu Chou, Danni Chen, Jiaze Yu, Yuzhen Chen, Feiran Jiao, Yi Xin, Lingyun Huang, Guotong Xie, Jing Xiao, Le Lu, Senxiang Yan, Dakai Jin^, Tsung-Ying Ho^.[pdf]

[MICCAI] SAME: Deformable Image Registration based on Self-supervised Anatomical Embeddings. Fengze Liu*, Ke Yan*, Adam Harrison, Dazhou Guo, Le Lu, Alan Yuille, Lingyun Huang, Guotong Xie, Jing Xiao, Xianghua Ye, Dakai Jin. (*equal contribution)

[MICCAI] DeepStationing: Thoracic Lymph Node Station Parsing in CT Scans using Anatomical Context Encoding and Key Organ Auto-Search. Dazhou Guo*, Xianghua Ye*, Jia Ge, Xing Di, Le Lu, Lingyun Huang, Guotong Xie, Jing Xiao, Zhongjie Lu, Ling Peng, Senxiang Yan, Dakai Jin. (*equal contribution)

[Frontiers in Radiology] CT-based risk factors for mortality of patients with COVID-19 Pneumonia in Wuhan, China: a retrospective study. Xiang Li*, Nannan Li*, Zhen Chen*, Ling Zhang*, Ling Ye*, Dakai Jin, Liangxin Gao, Xinhui Liu, Bolin Lai, Jiawen Yao, Dazhou Guo, Hua Zhang, Le Lu, Jing Xiao, Lingyun Huang, Fen Ai, Xiang Wang. (*equal contribution)

[ASTRO] Comprehensive Head and Neck Organs at Risk Segmentation using Stratified Learning and Neural Architecture Search, Head and Neck Cancer Track, POSTER VIEWING Q&A Session

[ASTRO] Anatomy Guided Thoracic Lymph Node Station Delineation in CT using Deep Learning Model, Digital Health Innovation Track, POSTER VIEWING Q&A Session

[ASTRO] Deep Learning Based Lymph Node Gross Tumor Volume Detection via Distance-guided Gating using CT and 18F-FDG PET in Esophageal Cancer Radiotherapy, Gastrointestinal Cancer Track, POSTER VIEWING Q&A Session

2020

[Medical Image Analysis] DeepTarget: Gross Tumor and Clinical Target Volume Segmentation in Esophageal Cancer Radiotherapy. Dakai Jin*, Dazhou Guo*, Tsung-Ying Ho, Adam P Harrison, Jing Xiao, Chen-kan Tseng, Le Lu. (MICCAI-2019 selected Papers Special Issue)
paper
[CVPR] Organ at Risk Segmentation for Head and Neck Cancer using Stratified Learning and Neural Architecture Search. Dazhou Guo, Dakai Jin, Zhuotun Zhu, Tsung-Ying Ho, Adam P Harrison, Chun-Hung Chao, Jing Xiao, Le Lu.
paper | poster | video
[MICCAI] Lymph Node Gross Tumor Volume Detection in Oncology Imaging via Relationship Learning Using Graph Neural Network. Chun-Hung Chao, Zhuotun Zhu, Dazhou Guo, Ke Yan, Tsung-Ying Ho, Jinzheng Cai, Adam P Harrison, Xianghua Ye, Jing Xiao, Alan Yuille, Min Sun, Le Lu, Dakai Jin. (Early accept)
paper
[MICCAI] 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, Tsung-Ying Ho, Xianghua Ye, Dazhou Guo, Chun-Hung Chao, Jing Xiao, Alan Yuille, Le Lu. (Early accept)
paper | poster | video
[Neurocomputing] Weakly supervised easy-to-hard learning for object detection in image sequences. Hongkai Yu, Dazhou Guo, Zhipeng Yan, Lan Fu, Jeff Simmons, Craig P Przybyla, Song Wang.
paper
[RSNA] Organs at Risk Segmentation for Head and Neck Cancer Using Stratified Learning and Neural Architecture Search. Tsung-Ying Ho, Dazhou Guo, Dakai Jin, Chien-Yu Lin, Le Lu, Tzu-Chen Yen, Jing Xiao. (Oral presentation)
[RSNA] Automated Esophageal Clinical Target Volume Delineation using Encoded 3D Spatial Context of Tumors, Lymph Nodes, and Organs At Risk. Tsung-Ying Ho, Dakai Jin, Dazhou Guo, Chen Kan Tseng, Le Lu, Tzu-Chen Yen, Jing Xiao. (Oral presentation)

2019

[MICCAI] Accurate Esophageal Gross Tumor Volume Segmentation in PET/CT Using Two-Stream Chained 3D Deep Network Fusion. Dakai Jin, Dazhou Guo, Tsung-Ying Ho, Adam P Harrison, Jing Xiao, Chen-kan Tseng, Le Lu. (Early accept and oral presentation)
paper | poster
[MICCAI] 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, Adam P Harrison, Jing Xiao, Chen-kan Tseng, Le Lu. (Early accept)
paper | poster
[Neurocomputing] An easy-to-hard learning strategy for within-image co-saliency detection. Shaoyue Song, Hongkai Yu, Zhenjiang Miao, Dazhou Guo, Wei Ke,Cong Ma, Song Wang. 2019
paper
[IEEE TIP] Degraded Image Semantic Segmentation With Dense-Gram Networks. Dazhou Guo, Yanting Pei, Kang Zheng, Hongkai Yu, Yuhang Lu, Song Wang.
paper | code | data
[IEEE TIP] Small Object Sensitive Segmentation of Urban Street Scene With Spatial Adjacency Between Object Classes. Dazhou Guo, Ligeng Zhu, Yuhang Lu, Hongkai Yu, Song Wang.
paper | code

Earlier

[ICCV] Learning View-Invariant Features for Person Identification in Temporally Synchronized Videos Taken by Wearable Cameras. Kang Zheng, Xiaochuan Fan, Yuewei Lin, Hao Guo, Hongkai Yu, Dazhou Guo, Song Wang.
paper | data
[BMC Medical Imaging] Automated lesion detection on MRI scans using combined unsupervised and supervised methods. Dazhou Guo, Julius Fridriksson, Paul Fillmore, Christopher Rorden, Hongkai Yu, Kang Zheng, Song Wang.
paper | code
[Frontiers in Human Neuroscience] Regional white matter damage predicts speech fluency in chronic post-stroke aphasia. Alexandra Basilakos, Paul Fillmore, Christopher Rorden, Dazhou Guo, Leonardo Bonilha, Julius Fridriksson.
paper
[Cerebral Cortex] Chronic Broca's Aphasia Is Caused by Damage to Broca's and Wernicke's Areas. Julius Fridriksson Paul Fillmore, Dazhou Guo, Christopher Rorden.
paper
[ECCV Workshop] Video-Based Action Detection Using Multiple Wearable Cameras. Kang Zheng, Yuewei Lin, Youjie Zhou, Dhaval Salvi, Xiaochuan Fan, Dazhou Guo, Zibo Meng, Song Wang.
paper
[Brain] Damage to the anterior arcuate fasciculus predicts non-fluent speech production in aphasia. Julius Fridriksson, Dazhou Guo, Paul Fillmore, Audrey Holland, Christopher Rorden.
paper