About Me

I received a BSc (2009) degree from China Agricultural University (CAU), Beijing, China, an MSc (2012) degree in Signal Processing from Xidian University, Xi'an, China and a PhD degree (2017) in Computer Science from University of Groningen, the Netherlands. I'm currently a Postdoc researcher at the University Medical Center Groningen, University of Groningen, the Netherlands. My current research interests include patten recognition, machine learning, brain-inspired computer vision, and their applications in medical image informatics.

    Awards
  • Data Scientist Grant from RUG Research and Innovation Center (2020), in University of Groningen
  • NVIDIA GPU Grant Programe (2018)
  • Won the scholarship of China Scholarship Council (2012-2016), in University of Groningen
  • Won the second prize Scholarship of 2009-2012, in Xidian University
  • Won the progress prize and the second prize Scholarship of 2005-2009, in CAU
  • Won the second prize of Campus Electronic Design Contest, in CAU.

Experience

Medical Image Analysis

Medical Imaging Informatics in Radiology and Radiation Oncology

My postdoc research focuses mainly on Medical Imaging Informatics, in which we develop deep learning models for prognostic outcome prediction for head and neck patients. Besides, I also collaborate with several PhD students on the development of Machine Learning algorithms for automatic medical image analysis on early diagnosis of Big-3 diseases in low dose CT scans and mandible segmentation for Maxillofacial Oncology..

Medical Image Analysis

Retina fundus image analysis for assisting glaucoma screening

Glaucoma is the second-leading cause of blindness. It damages the optic nerve irreversibly and has no early symptoms. The most common clinical measure is the cup-to-disc ratio. In collaboration with the Department of Ophthalmology of the University Medical Center Groningen, we develop more comprehensive methods to be used for large-scale glaucoma screening of the population.

Medical Image Analysis

Serrated patterns analysis in direct immunofluorescence images

The classification of serrated patterns in direct immunofluorescence images is used for the diagnosis of epidermolysis bullosa acquisita, a subepidermal autoimmune blistering disease of the skin. Together with the Department of Dermatology of the UMCG, we developed an automatic method to classify serrated patterns as u- or n-shaped.

Machine Learning

Brain-inspired computer vision

In my PhD research, I focused on brain-inspired computational models for pattern recognition. I proposed an inhibition-augmented trainble filters to improve their ability in discriminating similar patterns.

Machine Learning

Few-shot learning for fine-grained image classification

In collaboration with an Australian university and a research institute, we aim at further improving the performances of the current metric-based few-shot learning approaches for fine-grained image classification..

Object Detection

Recognition of architectural and electrical symbols

The automatic recognition of symbols can be used to automatically convert scanned drawings into digital representations compatible with computer aided design software. We propose a novel approach to automatically recognize architectural and electrical symbols.

Education

PostDoc researcher 2017-now

University Medical Center Groningen

PhD Degree 2017

University of Groningen

My research is about brain-inspired computer vision, including computational visual models of feature and object recognition; medical image and data analysis; machine learning algorithms such as deep learning. Specifically, I focus on techniques and extend methods in the field of automatic computer-aided diagnosis system for assisting population based glaucoma screening.

Summer school etc. 2012-2016

University of Groningen

Attended several courses within the MSc of Computer Science at the University of Groningen: Neural Networks and Computational Intelligence, Image Processing, Pattern Recognition. Attended the International Computer Vision Summer School (ICVSS), Italy, 2013.

Master Degree - 2012

Xidian University

Computer Science Technologies (Signal and Information Processing)

Bachelor Degree - 2009

China Agricultural University

Electronic Information Engineering

Main conferences and events attended

Jan 2017

Computer Aided Medical Diagnostics (CAMED),Las Palmas, Gran Canaria

Presented the talk: "Automatic optic disc and cup segmentation in retinal fundus images for assisting glaucoma screening"

Oct 2015

8th GI Conference on Autonomous Systems, Cala Millor, Spain

Presented the talk and paper: "Automatic Optic Disk Localization and Diameter Estimation in Retinal Fundus Images"

Sep 2015

Computer Analysis of Images and Patterns: 16th International Conference (CAIP), Valletta, Malta

Presented the talk and paper:"Recognition of architectural and electrical symbols by COSFIRE filters with inhibition"

2013-2016

Many International Workshops in Allersmaborg, Groningen, the Netherlands

My Projects

  • All
  • Medical Image Analysis
  • Brain-inspired computer vision
  • Machine learning

Publications

[1] Xiaonan Cui Mieneke Rook Raymond N. J. Veldhuis Matthijs Oudkerk Sunyi Zheng, Jiapan Guo and Peter M.A. van Ooijen. Automatic Pulmonary Nodule Detection in Low-Dose CT Scans Using Multi-Projection Textural Convolutional Neural Networks. IEEE Trans Medical Imaging, 39 (3):797-805, 2020. [ bib ]
[2] Rook M. Pelgrim G. J. Sidorenkov G. Wisselink H. J. van Bolhuis J. N. van Ooijen P. M. A. Guo, J. Oudkerk ... Vliegenthart R Xia, C. Early imaging biomarkers of lung cancer, COPD and coronary artery disease in the general population: rationale and design of the ImaLife (Imaging in Lifelines) Study. European Journal of Epidemiology, 35(1):75-86, 2020. [ bib ]
[3] Joep Kraeima Ronald Borra Max Witjes Bingjiang Qiu, Jiapan Guo and Peter M.A van Ooijen. Automatic segmentation of the mandible from computed tomography scans for 3D virtual surgical planning using the convolutional neural network. Physics in Medicine and Biology, 64(17), 2019. [ bib ]
[5] Guo, J. Ding X. van Ooijen P. M. A. Zhang Y. Chen A. ... Xie X He, Y. Convolutional neural network to predict the local recurrence of giant cell tumor of bone after curettage based on pre-surgery magnetic resonance images. European Radiology, 29(10):5441-5451, 2019. [ bib ]
[5] Guo, J. Ding X. van Ooijen P. M. A. Zhang Y. Chen A. ... Xie X He, Y. Convolutional neural network to predict the local recurrence of giant cell tumor of bone after curettage based on pre-surgery magnetic resonance images. European Radiology, 29(10):5441-5451, 2019. [ bib ]
[6] Jiapan Guo, Chenyu Shi, George Azzopardi, Nomdo M. Jansonius, and Nicolai Petkov. Automatic optic disc and cup segmentation in retinal fundus images for assisting glaucoma screening. IEEE Access, 7:8527-8541, 2019. [ bib ]
[7] Jiapan Guo George Azzopardi Gilles F.H. Diercksr Enno Schmidt Detlef Zillikens Marcel Jonkman Chenyu Shi*, Joost M. Meijer and Nicolai Petkov. Detection of u-serrated patterns in direct immuno?uorescence images of autoimmune bullous diseases by inhibitionaugmented COSFIRE ?lters. International Journal of Medical Informatics, 122:27-36, 2019. [ bib ]
[8] Jiapan Guo, Chenyu Shi, George Azzopardi, and Nicolai Petkov. Inhibition-augmented trainable COSFIRE filters for keypoint detection and object recognition. Machine Vision and Applications, 27(8):1197-1211, 2016. [ bib ]
[9] Jiapan Guo, Chenyu Shi, George Azzopardi, and Nicolai Petkov. An inhibition-augmented COSFIRE model of shape-selective neurons. IBM journal special issue on Computational Neuroscience, Accepted. [ bib ]
[10] Jiapan Guo, Chenyu Shi, George Azzopardi, and Nicolai Petkov. Recognition of architectural and electrical symbols by COSFIRE filters with inhibition. In Computer Analysis of Images and Patterns, volume 9257 of Lecture Notes in Computer Science, pages 348-358. Springer International Publishing, 2015. [ bib ]
[11] Chenyu Shi, Jiapan Guo, George Azzopardi, Joost M. Meijer, Marcel F. Jonkman, and Nicolai Petkov. Automatic differentiation of u- and n-serrated patterns in direct immunofluorescence images. In Computer Analysis of Images and Patterns (CAIP 2015), volume 9256 of Lecture Notes in Computer Science, pages 513-521, 2015. [ bib ]
[12] Chenyu Shi, Joost M. Meijer, Jiapan Guo, George Azzopardi, Marcel F. Jonkman, and Nicolai Petkov. Automatic classification of serrated patterns in direct immunofluorescence images. In 8th GI Conference on Autonomous Systems, volume 842, pages 61-69, 2015. [ bib ]
[13] Jiapan Guo, Chenyu Shi, Nomdo M. Jansonius, and Nicolai Petkov. Automatic Optic Disk Localization and Diameter Estimation in Retinal Fundus Images. In 8th GI Conference on Autonomous Systems, volume 842, pages 70-79, 2015. [ bib ]