Two graph theory based methods for identifying the pectoral muscle in mammograms F Ma, M Bajger, JP Slavotinek, MJ Bottema Pattern Recognition 40 (9), 2592-2602, 2007 | 102 | 2007 |
Spatial shape constrained fuzzy c-means (FCM) clustering for nucleus segmentation in pap smear images R Saha, M Bajger, G Lee 2016 international conference on digital image computing: techniques and …, 2016 | 43 | 2016 |
On the structure of some flows on the unit circle M Bajger Aequationes Mathematicae 55 (1-2), 106-121, 1998 | 29 | 1998 |
Low-error, high-speed approximation of the sigmoid function for large FPGA implementations M Bajger, A Omondi Journal of Signal Processing Systems 52, 137-151, 2008 | 28 | 2008 |
FPGA neurocomputers AR Omondi, JC Rajapakse, M Bajger FPGA Implementations of Neural Networks, 1-36, 2006 | 28 | 2006 |
Circular shape constrained fuzzy clustering (CiscFC) for nucleus segmentation in Pap smear images R Saha, M Bajger, G Lee Computers in Biology and Medicine 85, 13-23, 2017 | 25 | 2017 |
Minimum spanning trees and active contours for identification of the pectoral muscle in screening mammograms M Bajger, F Ma, MJ Bottema Digital Image Computing: Techniques and Applications (DICTA'05), 47-47, 2005 | 22 | 2005 |
Segmentation of breast masses in local dense background using adaptive clip limit-CLAHE S Sajeev, M Bajger, G Lee 2015 International Conference on Digital Image Computing: Techniques and …, 2015 | 20 | 2015 |
Mammographic mass detection with statistical region merging M Bajger, F Ma, S Williams, M Bottema 2010 international conference on digital image computing: Techniques and …, 2010 | 17 | 2010 |
Automatic tuning of MST segmentation of mammograms for registration and mass detection algorithms M Bajger, F Ma, MJ Bottema 2009 Digital Image Computing: Techniques and Applications, 400-407, 2009 | 16 | 2009 |
3D segmentation for multi-organs in CT images M Bajger, G Lee, M Caon Electronic Letters on Computer Vision and Image Analysis 12 (2), 13-27, 2013 | 14 | 2013 |
Automatic mass segmentation based on adaptive pyramid and sublevel set analysis F Ma, M Bajger, MJ Bottema 2009 Digital Image Computing: Techniques and Applications, 236-241, 2009 | 14 | 2009 |
Extracting the pectoral muscle in screening mammograms using a graph pyramid F Ma, M Bajger, M Bottema APRS workshop on digital image computing, 2005 | 13 | 2005 |
Computer-assisted segmentation of CT images by statistical region merging for the production of voxel models of anatomy for CT dosimetry M Caon, J Sedlář, M Bajger, G Lee Australasian Physical & Engineering Sciences in Medicine 37, 393-403, 2014 | 12 | 2014 |
Multi-organ segmentation of CT images using statistical region merging GN Lee, M Bajger, M Caon 9th IASTED International Conference on Biomedical Engineering BioMed 2012 …, 2012 | 12 | 2012 |
Robustness of two methods for segmenting salient features in screening mammograms F Ma, M Bajger, MJ Bottema 9th Biennial Conference of the Australian Pattern Recognition Society on …, 2007 | 11 | 2007 |
SRM superpixel merging framework for precise segmentation of cervical nucleus R Saha, M Bajger, G Lee 2019 Digital Image Computing: Techniques and Applications (DICTA), 1-8, 2019 | 10 | 2019 |
Segmentation of cervical nuclei using SLIC and pairwise regional contrast R Saha, M Bajger, G Lee 2018 40th Annual international conference of the IEEE Engineering in …, 2018 | 10 | 2018 |
Prior guided segmentation and nuclei feature based abnormality detection in cervical cells R Saha, M Bajger, G Lee 2019 IEEE 19th international conference on bioinformatics and bioengineering …, 2019 | 8 | 2019 |
Deep learning and color variability in breast cancer histopathological images: a preliminary study G Lee, M Bajger, K Clark 14th International Workshop on Breast Imaging (IWBI 2018) 10718, 370-375, 2018 | 8 | 2018 |