Silvia D. Chang
According to our database1,
Silvia D. Chang
authored at least 28 papers
between 2013 and 2024.
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Bibliography
2024
LensePro: label noise-tolerant prototype-based network for improving cancer detection in prostate ultrasound with limited annotations.
Int. J. Comput. Assist. Radiol. Surg., June, 2024
2023
Comput. methods Biomech. Biomed. Eng. Imaging Vis., July, 2023
2022
Coarse label refinement for improving prostate cancer detection in ultrasound imaging.
Int. J. Comput. Assist. Radiol. Surg., 2022
Training deep neural networks with noisy clinical labels: toward accurate detection of prostate cancer in US data.
Int. J. Comput. Assist. Radiol. Surg., 2022
Towards targeted ultrasound-guided prostate biopsy by incorporating model and label uncertainty in cancer detection.
Int. J. Comput. Assist. Radiol. Surg., 2022
Uncertainty-Aware Deep Ensemble Model For Targeted Ultrasound-Guided Prostate Biopsy.
Proceedings of the 19th IEEE International Symposium on Biomedical Imaging, 2022
2021
Training Deep Networks for Prostate Cancer Diagnosis Using Coarse Histopathological Labels.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2021 - 24th International Conference, Strasbourg, France, September 27, 2021
Characterizing The Uncertainty Of Label Noise In Systematic Ultrasound-Guided Prostate Biopsy.
Proceedings of the 18th IEEE International Symposium on Biomedical Imaging, 2021
2020
A partial augmented reality system with live ultrasound and registered preoperative MRI for guiding robot-assisted radical prostatectomy.
Medical Image Anal., 2020
Multiple instance learning combined with label invariant synthetic data for guiding systematic prostate biopsy: a feasibility study.
Int. J. Comput. Assist. Radiol. Surg., 2020
Complex Cancer Detector: Complex Neural Networks on Non-stationary Time Series for Guiding Systematic Prostate Biopsy.
Proceedings of the Medical Image Computing and Computer Assisted Intervention - MICCAI 2020, 2020
2016
Classification of prostate cancer grade using temporal ultrasound: in vivo feasibility study.
Proceedings of the Medical Imaging 2016: Image-Guided Procedures, Robotic Interventions, and Modeling, San Diego, California, United States, 27 February, 2016
Fusion of multi-parametric MRI and temporal ultrasound for characterization of prostate cancer: in vivo feasibility study.
Proceedings of the Medical Imaging 2016: Computer-Aided Diagnosis, San Diego, 2016
2015
Biomechanically Constrained Surface Registration: Application to MR-TRUS Fusion for Prostate Interventions.
IEEE Trans. Medical Imaging, 2015
Statistical Biomechanical Surface Registration: Application to MR-TRUS Fusion for Prostate Interventions.
IEEE Trans. Medical Imaging, 2015
Computer-Aided Prostate Cancer Detection Using Ultrasound RF Time Series: In Vivo Feasibility Study.
IEEE Trans. Medical Imaging, 2015
Ultrasound-Based Characterization of Prostate Cancer Using Joint Independent Component Analysis.
IEEE Trans. Biomed. Eng., 2015
A data-driven approach to prostate cancer detection from dynamic contrast enhanced MRI.
Comput. Medical Imaging Graph., 2015
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2015, 2015
Prostate cancer detection from model-free T1-weighted time series and diffusion imaging.
Proceedings of the Medical Imaging 2015: Computer-Aided Diagnosis, 2015
2014
Registration of Whole-Mount Histology and Volumetric Imaging of the Prostate Using Particle Filtering.
IEEE Trans. Medical Imaging, 2014
Towards enabling ultrasound guidance in cervical cancer high-dose-rate brachytherapy.
Proceedings of the Medical Imaging 2014: Image-Guided Procedures, 2014
Proceedings of the Medical Imaging 2014: Image-Guided Procedures, 2014
Improved parameter extraction and classification for dynamic contrast enhanced MRI of prostate.
Proceedings of the Medical Imaging 2014: Computer-Aided Diagnosis, San Diego, 2014
Filter-Based Speckle Tracking for Freehand Prostate Biopsy: Theory, ex vivo and in vivo Results.
Proceedings of the Information Processing in Computer-Assisted Interventions, 2014
2013
Model-Based Registration of Ex Vivo and In Vivo MRI of the Prostate Using Elastography.
IEEE Trans. Medical Imaging, 2013
Ultrasound-Based Characterization of Prostate Cancer: An in vivo Clinical Feasibility Study.
Proceedings of the Medical Image Computing and Computer-Assisted Intervention - MICCAI 2013, 2013