publications

2024

1. A semi-automatic segmentation method for meningioma developed using a variational approach model

   Liam Burrows, Jay Patel, Abdurrahman I Islim, and 3 more authors

   The neuroradiology journal, 2024

   Bib

   @article{burrows2024semi,
     title = {A semi-automatic segmentation method for meningioma developed using a variational approach model},
     author = {Burrows, Liam and Patel, Jay and Islim, Abdurrahman I and Jenkinson, Michael D and Mills, Samantha J and Chen, Ke},
     journal = {The neuroradiology journal},
     volume = {37},
     number = {2},
     pages = {199--205},
     year = {2024},
     publisher = {SAGE Publications Sage UK: London, England}
   }

2. Mathematical modelling and deep learning algorithms to automate assessment of single and digitally multiplexed immunohistochemical stains in tumoural stroma

   Liam Burrows, Declan Sculthorpe, Hongrun Zhang, and 3 more authors

   Journal of Pathology Informatics, 2024

   Bib

   @article{burrows2024mathematical,
     title = {Mathematical modelling and deep learning algorithms to automate assessment of single and digitally multiplexed immunohistochemical stains in tumoural stroma},
     author = {Burrows, Liam and Sculthorpe, Declan and Zhang, Hongrun and Rehman, Obaid and Mukherjee, Abhik and Chen, Ke},
     journal = {Journal of Pathology Informatics},
     volume = {15},
     pages = {100351},
     year = {2024},
     publisher = {Elsevier}
   }

2023

1. 

   Weakly supervised segmentation with point annotations for histopathology images via contrast-based variational model

   Hongrun Zhang, Liam Burrows, Yanda Meng, and 5 more authors

   In Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition , 2023

   Bib

   @inproceedings{zhang2023weakly,
     title = {Weakly supervised segmentation with point annotations for histopathology images via contrast-based variational model},
     author = {Zhang, Hongrun and Burrows, Liam and Meng, Yanda and Sculthorpe, Declan and Mukherjee, Abhik and Coupland, Sarah E and Chen, Ke and Zheng, Yalin},
     booktitle = {Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
     pages = {15630--15640},
     year = {2023},
   }

2022

1. On two convex variational models and their iterative solutions for selective segmentation of images with intensity inhomogeneity

   Liam Burrows, Ke Chen, and Francesco Torella

   Computational Mathematics and Computer Modeling with Applications (CMCMA), 2022

   Bib Code

   @article{burrows2022two,
     title = {On two convex variational models and their iterative solutions for selective segmentation of images with intensity inhomogeneity},
     author = {Burrows, Liam and Chen, Ke and Torella, Francesco},
     journal = {Computational Mathematics and Computer Modeling with Applications (CMCMA)},
     volume = {1},
     number = {2},
     pages = {86--103},
     year = {2022},
     publisher = {Computational Mathematics and Computer Modeling with Applications (CMCMA)},
   }

2. 

   Evaluation of a hybrid pipeline for automated segmentation of solid lesions based on mathematical algorithms and deep learning

   Liam Burrows, Ke Chen, Weihong Guo, and 3 more authors

   Scientific Reports, 2022

   Bib

   @article{burrows2022evaluation,
     title = {Evaluation of a hybrid pipeline for automated segmentation of solid lesions based on mathematical algorithms and deep learning},
     author = {Burrows, Liam and Chen, Ke and Guo, Weihong and Hossack, Martin and McWilliams, Richard G and Torella, Francesco},
     journal = {Scientific Reports},
     volume = {12},
     number = {1},
     pages = {14216},
     year = {2022},
     publisher = {Nature Publishing Group UK London},
   }

2021

1. Selective segmentation of a feature that has two distinct intensities

   Liam Burrows, Ke Chen, and Francesco Torella

   Journal of Algorithms & Computational Technology, 2021

   Bib

   @article{burrows2021selective,
     title = {Selective segmentation of a feature that has two distinct intensities},
     author = {Burrows, Liam and Chen, Ke and Torella, Francesco},
     journal = {Journal of Algorithms \& Computational Technology},
     volume = {15},
     pages = {17483026211007776},
     year = {2021},
     publisher = {SAGE Publications Sage UK: London, England}
   }

2. A deep image prior learning algorithm for joint selective segmentation and registration

   Liam Burrows, Ke Chen, and Francesco Torella

   In International Conference on Scale Space and Variational Methods in Computer Vision , 2021

   Bib

   @inproceedings{burrows2021deep,
     title = {A deep image prior learning algorithm for joint selective segmentation and registration},
     author = {Burrows, Liam and Chen, Ke and Torella, Francesco},
     booktitle = {International Conference on Scale Space and Variational Methods in Computer Vision},
     pages = {411--422},
     year = {2021},
     organization = {Springer}
   }

3. On a variational and convex model of the Blake–Zisserman type for segmentation of low-contrast and piecewise smooth images

   Liam Burrows, Anis Theljani, and Ke Chen

   Journal of Imaging, 2021

   Bib Code

   @article{burrows2021variational,
     title = {On a variational and convex model of the Blake--Zisserman type for segmentation of low-contrast and piecewise smooth images},
     author = {Burrows, Liam and Theljani, Anis and Chen, Ke},
     journal = {Journal of Imaging},
     volume = {7},
     number = {11},
     pages = {228},
     year = {2021},
     publisher = {MDPI},
   }

4. Using deep image prior to assist variational selective segmentation deep learning algorithms

   Liam Burrows, Ke Chen, and Francesco Torella

   In 17th International Symposium on Medical Information Processing and Analysis , 2021

   Bib Code

   @inproceedings{burrows2021using,
     title = {Using deep image prior to assist variational selective segmentation deep learning algorithms},
     author = {Burrows, Liam and Chen, Ke and Torella, Francesco},
     booktitle = {17th International Symposium on Medical Information Processing and Analysis},
     volume = {12088},
     pages = {243--252},
     year = {2021},
     organization = {SPIE},
   }

2020

1. Edge enhancement for image segmentation using a RKHS method

   Liam Burrows, Weihong Guo, Ke Chen, and 1 more author

   In Medical Image Understanding and Analysis: 23rd Conference, MIUA 2019, Liverpool, UK, July 24–26, 2019, Proceedings 23 , 2020

   Bib

   @inproceedings{burrows2020edge,
     title = {Edge enhancement for image segmentation using a RKHS method},
     author = {Burrows, Liam and Guo, Weihong and Chen, Ke and Torella, Francesco},
     booktitle = {Medical Image Understanding and Analysis: 23rd Conference, MIUA 2019, Liverpool, UK, July 24--26, 2019, Proceedings 23},
     pages = {198--207},
     year = {2020},
     organization = {Springer}
   }

2. On new convolutional neural network based algorithms for selective segmentation of images

   Liam Burrows, Ke Chen, and Francesco Torella

   In Medical Image Understanding and Analysis: 24th Annual Conference, MIUA 2020, Oxford, UK, July 15-17, 2020, Proceedings 24 , 2020

   Bib

   @inproceedings{burrows2020new,
     title = {On new convolutional neural network based algorithms for selective segmentation of images},
     author = {Burrows, Liam and Chen, Ke and Torella, Francesco},
     booktitle = {Medical Image Understanding and Analysis: 24th Annual Conference, MIUA 2020, Oxford, UK, July 15-17, 2020, Proceedings 24},
     pages = {93--104},
     year = {2020},
     organization = {Springer}
   }

3. 

   Reproducible kernel Hilbert space based global and local image segmentation

   Liam Burrows, Weihong Guo, Ke Chen, and 1 more author

   Inverse Problems & Imaging, 2020

   Bib Code

   @article{burrows2020reproducible,
     title = {Reproducible kernel Hilbert space based global and local image segmentation},
     author = {Burrows, Liam and Guo, Weihong and Chen, Ke and Torella, Francesco},
     journal = {Inverse Problems \& Imaging},
     year = {2020},
   }