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2024

Journal Article

Synthetic data for deep learning in computer vision and medical imaging: a means to reduce data bias

Paproki, Anthony, Salvado, Olivier and Fookes, Clinton (2024). Synthetic data for deep learning in computer vision and medical imaging: a means to reduce data bias. ACM Computing Surveys, 56 (11) 271, 1-37. doi: 10.1145/3663759

Synthetic data for deep learning in computer vision and medical imaging: a means to reduce data bias

2023

Conference Publication

Learning dense correspondence from synthetic environments

Lal, Mithun, Paproki, Anthony, Habili, Nariman, Petersson, Lars, Salvado, Olivier and Fookes, Clinton (2023). Learning dense correspondence from synthetic environments. 2022 International Conference on Digital Image Computing: Techniques and Applications (DICTA), Sydney, NSW Australia, 30 November-2 December 2022. Piscataway, NJ USA: Institute of Electrical and Electronics Engineers. doi: 10.1109/dicta56598.2022.10034586

Learning dense correspondence from synthetic environments

2021

Journal Article

Time to get serious about the detection and monitoring of early lung disease in cystic fibrosis

Bayfield, Katie J., Douglas, Tonia A., Rosenow, Tim, Davies, Jane Carolyn, Elborn, Stuart J., Mall, Marcus, Paproki, Anthony, Ratjen, Felix, Sly, Peter D., Smyth, Alan R., Stick, Stephen, Wainwright, Claire E. and Robinson, Paul D. (2021). Time to get serious about the detection and monitoring of early lung disease in cystic fibrosis. Thorax, 76 (12), 1-11. doi: 10.1136/thoraxjnl-2020-216085

Time to get serious about the detection and monitoring of early lung disease in cystic fibrosis

2018

Journal Article

A lightweight rapid application development framework for biomedical image analysis

Chandra, Shekhar S., Dowling, Jason A., Engstrom, Craig, Xia, Ying, Paproki, Anthony, Neubert, Aleš, Rivest-Hénault, David, Salvado, Olivier, Crozier, Stuart and Fripp, Jurgen (2018). A lightweight rapid application development framework for biomedical image analysis. Computer Methods and Programs in Biomedicine, 164, 193-205. doi: 10.1016/j.cmpb.2018.07.011

A lightweight rapid application development framework for biomedical image analysis

2017

Journal Article

Automated T2-mapping of the Menisci From Magnetic Resonance Images in Patients with Acute Knee Injury

Paproki, Anthony, Engstrom, Craig, Strudwick, Mark, Wilson, Katharine J., Surowiec, Rachel K., Ho, Charles, Crozier, Stuart and Fripp, Jurgen (2017). Automated T2-mapping of the Menisci From Magnetic Resonance Images in Patients with Acute Knee Injury. Academic Radiology, 24 (10), 1295-1304. doi: 10.1016/j.acra.2017.03.025

Automated T2-mapping of the Menisci From Magnetic Resonance Images in Patients with Acute Knee Injury

2017

Journal Article

Comparison of 3D bone models of the knee joint derived from CT and 3T MR imaging

Neubert, Aleš, Wilson, Katharine J., Engstrom, Craig, Surowiec, Rachel K., Paproki, Anthony, Johnson, Nicholas, Crozier, Stuart, Fripp, Jurgen and Ho, Charles P. (2017). Comparison of 3D bone models of the knee joint derived from CT and 3T MR imaging. European Journal of Radiology, 93, 178-184. doi: 10.1016/j.ejrad.2017.05.042

Comparison of 3D bone models of the knee joint derived from CT and 3T MR imaging

2017

Other Outputs

Automated Image Analysis of High-field and Dynamic Musculoskeletal MRI

Paproki, Anthony (2017). Automated Image Analysis of High-field and Dynamic Musculoskeletal MRI. PhD Thesis, School of Information Technol and Elec Engineering, The University of Queensland. doi: 10.14264/uql.2017.388

Automated Image Analysis of High-field and Dynamic Musculoskeletal MRI

2016

Conference Publication

Automated segmentation and T2-mapping of the posterior cruciate ligament from MRI of the knee: data from the osteoarthritis initiative

Paproki, Anthony, Wilson, Katharine J., Surowiec, Rachel K., Ho, Charles P., Pant, Abinash, Bourgeat, Pierrick, Engstrom, Craig, Crozier, Stuart and Fripp, Jurgen (2016). Automated segmentation and T2-mapping of the posterior cruciate ligament from MRI of the knee: data from the osteoarthritis initiative. IEEE International Symposium on Biomedical Imaging (ISBI), Prague, Czech Republic, 13-16 April 2016. Piscataway, NJ, United States: IEEE. doi: 10.1109/ISBI.2016.7493298

Automated segmentation and T2-mapping of the posterior cruciate ligament from MRI of the knee: data from the osteoarthritis initiative

2016

Conference Publication

Incremental shape learning of 3D surfaces of the knee, data from the osteoarthritis initiative

Neubert, Ales, Naser, Ibrahim, Paproki, Anthony, Engstrom, Craig, Fripp, Jurgen, Crozier, Stuart and Chandra, Shekhar S. (2016). Incremental shape learning of 3D surfaces of the knee, data from the osteoarthritis initiative. 2016 IEEE 13th International Symposium on Biomedical Imaging (ISBI), Prague, Czech Republic, 13-16 April, 2016. Piscataway, United States: IEEE Operations Center. doi: 10.1109/ISBI.2016.7493406

Incremental shape learning of 3D surfaces of the knee, data from the osteoarthritis initiative

2015

Journal Article

Automatic bone segmentation and bone-cartilage interface extraction for the shoulder joint from magnetic resonance images

Yang, Zhengyi, Fripp, Jurgen, Chandra, Shekhar S., Neubert, Ales, Xia, Ying, Strudwick, Mark, Paproki, Anthony, Engstrom, Craig and Crozier, Stuart (2015). Automatic bone segmentation and bone-cartilage interface extraction for the shoulder joint from magnetic resonance images. Physics in Medicine and Biology, 60 (4), 1441-1459. doi: 10.1088/0031-9155/60/4/1441

Automatic bone segmentation and bone-cartilage interface extraction for the shoulder joint from magnetic resonance images

2014

Conference Publication

Automatic Bone Segmentation for Shoulder {MRI} using Statistical Shape Models

Yang, Zhengyi, Fripp, Jurgen, Engstrom, Craig, Chandra, Shekhar, Xia, Ying, Paproki, Anthony, Strudwick, Mark, Neubert, Ales and Crozier, Stuart (2014). Automatic Bone Segmentation for Shoulder {MRI} using Statistical Shape Models. 2014 – Joint Annual Meeting ISMRM-ESMRMB, 22nd Scientific Meeting and Exhibition, Milan, Italy, 10-16 May 2014. Berkeley, CA United States: International Society for Magnetic Resonance in Medicine.

Automatic Bone Segmentation for Shoulder {MRI} using Statistical Shape Models

2014

Journal Article

Automated segmentation and analysis of normal and osteoarthritic knee menisci from magnetic resonance images: data from the Osteoarthritis Initiative

Paproki, A., Engstrom, C., Chandra, S. S., Neubert, A., Fripp, J. and Crozier, S. (2014). Automated segmentation and analysis of normal and osteoarthritic knee menisci from magnetic resonance images: data from the Osteoarthritis Initiative. Osteoarthritis and Cartilage, 22 (9), 1259-1270. doi: 10.1016/j.joca.2014.06.029

Automated segmentation and analysis of normal and osteoarthritic knee menisci from magnetic resonance images: data from the Osteoarthritis Initiative

2012

Journal Article

A novel mesh processing based technique for 3D plant analysis

Paproki, Anthony, Sirault, Xavier, Berry, Scott, Furbank, Robert and Fripp, Jurgen (2012). A novel mesh processing based technique for 3D plant analysis. Bmc Plant Biology, 12 63. doi: 10.1186/1471-2229-12-63

A novel mesh processing based technique for 3D plant analysis

2011

Conference Publication

Automated 3D segmentation and analysis of cotton plants

Paproki, Anthony, Fripp, Jurgen, Salvado, Olivier, Sirault, Xavier, Berry, Scott and Furbank, Robert (2011). Automated 3D segmentation and analysis of cotton plants. 2011 International Conference on Digital Image Computing: Techniques and Applications, Noosa, QLD Australia, 6-8 December 2011. Piscataway, NJ USA: Institute of Electrical and Electronics Engineers. doi: 10.1109/dicta.2011.99

Automated 3D segmentation and analysis of cotton plants