John Kurhanewicz

According to our database1, John Kurhanewicz authored at least 14 papers between 2009 and 2018.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
Other 

Links

On csauthors.net:

Bibliography

2018
Spatio-Temporally Constrained Reconstruction for Hyperpolarized Carbon-13 MRI Using Kinetic Models.
IEEE Trans. Med. Imaging, 2018

2014
High Resolution $^{13}$C MRI With Hyperpolarized Urea: In Vivo $T_{2}$ Mapping and $^{15}$N Labeling Effects.
IEEE Trans. Med. Imaging, 2014

A domain constrained deformable (DoCD) model for co-registration of pre- and post-radiated prostate MRI.
Neurocomputing, 2014

A prostate MRI atlas of biochemical failures following cancer treatment.
Proceedings of the Medical Imaging 2014: Computer-Aided Diagnosis, 2014

Computer extracted texture features on T2w MRI to predict biochemical recurrence following radiation therapy for prostate cancer.
Proceedings of the Medical Imaging 2014: Computer-Aided Diagnosis, 2014

2013
Multi-kernel graph embedding for detection, Gleason grading of prostate cancer via MRI/MRS.
Medical Image Anal., 2013

2012
Generating Super Stimulated-Echoes in MRI and Their Application to Hyperpolarized C-13 Diffusion Metabolic Imaging.
IEEE Trans. Med. Imaging, 2012

2011
A magnetic resonance spectroscopy driven initialization scheme for active shape model based prostate segmentation.
Medical Image Anal., 2011

Weighted Combination of Multi-Parametric MR Imaging Markers for Evaluating Radiation Therapy Related Changes in the Prostate.
Proceedings of the Prostate Cancer Imaging. Image Analysis and Image-Guided Interventions, 2011

Variable Ranking with PCA: Finding Multiparametric MR Imaging Markers for Prostate Cancer Diagnosis and Grading.
Proceedings of the Prostate Cancer Imaging. Image Analysis and Image-Guided Interventions, 2011

CADOnc ©: An integrated toolkit for evaluating radiation therapy related changes in the prostate using multiparametric MRI.
Proceedings of the 8th IEEE International Symposium on Biomedical Imaging: From Nano to Macro, 2011

2010
Semi Supervised Multi Kernel (SeSMiK) Graph Embedding: Identifying Aggressive Prostate Cancer via Magnetic Resonance Imaging and Spectroscopy.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention, 2010

2009
Spectral Embedding Based Probabilistic Boosting Tree (ScEPTre): Classifying High Dimensional Heterogeneous Biomedical Data.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention, 2009

MRI-Ultrasound Registration for Targeted Prostate Biopsy.
Proceedings of the 2009 IEEE International Symposium on Biomedical Imaging: From Nano to Macro, Boston, MA, USA, June 28, 2009


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