Mariusz Bajger

Shaowen Qin

Proceedings of the Advanced Data Mining and Applications - 19th International Conference, 2023

2021

Texture enhanced Statistical Region Merging with application to automatic knee bones segmentation from CT.

[BibT_eX]

[DOI]

Proceedings of the 2021 Digital Image Computing: Techniques and Applications, 2021

Lumbar Spine CT synthesis from MR images using CycleGAN - a preliminary study.

[BibT_eX]

[DOI]

Proceedings of the 2021 Digital Image Computing: Techniques and Applications, 2021

Network Graph Analysis of Hospital and Health Services Functional Structures.

[BibT_eX]

[DOI]

Proceedings of the Advanced Data Mining and Applications - 17th International Conference, 2021

2020

On the Continuous Cancellative Semigroups on a Real Interval and on a Circle and Some Symmetry Issues.

[BibT_eX]

[DOI]

Symmetry, 2020

2019

Graph Modeling for Identifying Breast Tumor Located in Dense Background of a Mammogram.

[BibT_eX]

[DOI]

Proceedings of the Graph Learning in Medical Imaging - First International Workshop, 2019

SRM Superpixel Merging Framework for Precise Segmentation of Cervical Nucleus.

[BibT_eX]

[DOI]

Proceedings of the 2019 Digital Image Computing: Techniques and Applications, 2019

Prior Guided Segmentation and Nuclei Feature Based Abnormality Detection in Cervical Cells.

[BibT_eX]

[DOI]

Proceedings of the 19th IEEE International Conference on Bioinformatics and Bioengineering, 2019

Organs-at-Risk Contouring on Head CT for RT Planning Using 3D Slicer- A Preliminary Study.

[BibT_eX]

[DOI]

Proceedings of the 19th IEEE International Conference on Bioinformatics and Bioengineering, 2019

2018

Superpixel texture analysis for classification of breast masses in dense background.

[BibT_eX]

[DOI]

IET Comput. Vis., 2018

Paediatric Liver Segmentation for Low-Contrast CT Images.

[BibT_eX]

[DOI]

Martin Caon

Proceedings of the Data Driven Treatment Response Assessment - and - Preterm, Perinatal, and Paediatric Image Analysis, 2018

Superpixel pattern graphs for identifying breast mass ROIs in dense background: a preliminary study.

[BibT_eX]

[DOI]

Proceedings of the 14th International Workshop on Breast Imaging, 2018

Deep learning and color variability in breast cancer histopathological images: a preliminary study.

[BibT_eX]

[DOI]

Kevin Clark

Proceedings of the 14th International Workshop on Breast Imaging, 2018

Segmentation of cervical nuclei using SLIC and pairwise regional contrast.

[BibT_eX]

[DOI]

Proceedings of the 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, 2018

Circular Shape Prior in Efficient Graph Based Image Segmentation to Segment Nucleus.

[BibT_eX]

[DOI]

Proceedings of the 2018 Digital Image Computing: Techniques and Applications, 2018

2017

Circular shape constrained fuzzy clustering (CiscFC) for nucleus segmentation in Pap smear images.

[BibT_eX]

[DOI]

Comput. Biol. Medicine, 2017

Structured Micro-Pattern Based LBP Features for Classification of Masses in Dense Breasts.

[BibT_eX]

[DOI]

Proceedings of the 2017 International Conference on Digital Image Computing: Techniques and Applications, 2017

2016

Improving Breast Mass Segmentation in Local Dense Background: An Entropy Based Optimization of Statistical Region Merging Method.

[BibT_eX]

[DOI]

Proceedings of the Breast Imaging, 2016

Model-Guided Segmentation of Liver in CT and PET-CT Images of Child Patients Based on Statistical Region Merging.

[BibT_eX]

[DOI]

Proceedings of the 2016 International Conference on Digital Image Computing: Techniques and Applications, 2016

Spatial Shape Constrained Fuzzy C-Means (FCM) Clustering for Nucleus Segmentation in Pap Smear Images.

[BibT_eX]

[DOI]

Proceedings of the 2016 International Conference on Digital Image Computing: Techniques and Applications, 2016

2015

Incorporation of fuzzy spatial relation in temporal mammogram registration.

[BibT_eX]

[DOI]

Fuzzy Sets Syst., 2015

Segmentation of Breast Masses in Local Dense Background Using Adaptive Clip Limit-CLAHE.

[BibT_eX]

[DOI]

Proceedings of the 2015 International Conference on Digital Image Computing: Techniques and Applications, 2015

Mammogram Mass Classification with Temporal Features and Multiple Kernel Learning.

[BibT_eX]

[DOI]

Proceedings of the 2015 International Conference on Digital Image Computing: Techniques and Applications, 2015

2014

Statistical Temporal Changes for Breast Cancer Detection: A Preliminary Study.

[BibT_eX]

[DOI]

Proceedings of the Breast Imaging - 12th International Workshop, IWDM 2014, Gifu City, Japan, June 29, 2014

2010

Improved Detection of Cancer in Screening Mammograms by Temporal Comparison.

[BibT_eX]

[DOI]

Proceedings of the Digital Mammography, 2010

Mammographic Mass Detection with Statistical Region Merging.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Digital Image Computing: Techniques and Applications, 2010

2009

Automatic Mass Segmentation Based on Adaptive Pyramid and Sublevel Set Analysis.

[BibT_eX]

[DOI]

Proceedings of the DICTA 2009, 2009

Automatic Tuning of MST Segmentation of Mammograms for Registration and Mass Detection Algorithms.

[BibT_eX]

[DOI]

Proceedings of the DICTA 2009, 2009

2008

Low-error, High-speed Approximation of the Sigmoid Function for Large FPGA Implementations.

[BibT_eX]

[DOI]

Amos Omondi

J. Signal Process. Syst., 2008

A graph matching based automatic regional registration method for sequential mammogram analysis.

[BibT_eX]

[DOI]

Proceedings of the Medical Imaging 2008: Computer-Aided Diagnosis, 2008

Temporal Analysis of Mammograms Based on Graph Matching.

[BibT_eX]

[DOI]

Proceedings of the Digital Mammography, 2008

Automatic tuning of a graph-based image segmentation method for digital mammography applications.

[BibT_eX]

[DOI]

Hirotaka Susukida

Proceedings of the 2008 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2008

2007

Two graph theory based methods for identifying the pectoral muscle in mammograms.

[BibT_eX]

[DOI]

Pattern Recognit., 2007

Robustness of Two Methods for Segmenting Salient Features in Screening Mammograms.

[BibT_eX]

[DOI]

Proceedings of the International Conference on Digital Image Computing: Techniques and Applications, 2007

2006

Validation of Graph Theoretic Segmentation of the Pectoral Muscle.

[BibT_eX]

[DOI]

Proceedings of the Digital Mammography, 2006

Implementations of Square-Root and Exponential Functions for Large FPGAs.

[BibT_eX]

[DOI]

Amos Omondi

Proceedings of the Advances in Computer Systems Architecture, 11th Asia-Pacific Conference, 2006

2005

Minimum Spanning Trees and Active Contours for Identification of the Pectoral Muscle in Screening Mammograms.

[BibT_eX]

[DOI]