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Peter A. Pinto
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- affiliation: National Institutes of Health, Bethesda, MD, USA
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2020 – today
- 2024
- [j16]Boah Kim
, Tejas Sudharshan Mathai
Classification of Multi-Parametric Body MRI Series Using Deep Learning. IEEE J. Biomed. Health Informatics 28(11): 6791-6802 (2024) - [c25]Alex Chen, Nathan Lay, Stephanie A. Harmon, Kutsev Ozyoruk, Enis Yilmaz, Bradford J. Wood, Peter A. Pinto, Peter L. Choyke, Baris Turkbey:
Location-Based Radiology Report-Guided Semi-Supervised Learning for Prostate Cancer Detection. ISBI 2024: 1-5 - [i2]Alex Chen, Nathan Lay, Stephanie A. Harmon, Kutsev Ozyoruk, Enis Yilmaz, Bradford J. Wood, Peter A. Pinto, Peter L. Choyke, Baris Turkbey:
Location-based Radiology Report-Guided Semi-supervised Learning for Prostate Cancer Detection. CoRR abs/2406.12177 (2024) - 2023
- [c24]Akshaya Anand, Jianfei Liu, Thomas C. Shen, W. Marston Linehan, Peter A. Pinto, Ronald M. Summers:
Automated classification of intravenous contrast enhancement phase of CT scans using residual networks. Computer-Aided Diagnosis 2023 - 2021
- [j15]Samira Masoudi, Sherif Mehralivand, Stephanie A. Harmon, Nathan Lay, Liza Lindenberg, Esther Mena, Peter A. Pinto, Deborah E. Citrin
Deep Learning Based Staging of Bone Lesions From Computed Tomography Scans. IEEE Access 9: 87531-87542 (2021) - [c23]Samira Masoudi, Stephanie A. Harmon, Sherif Mehralivand, Nathan Lay, Ulas Bagci, Bradford J. Wood
No-Reference Image Quality Assessment Of T2-Weighted Magnetic Resonance Images In Prostate Cancer Patients. ISBI 2021: 1201-1205 - 2020
- [j14]Alireza Sedghi, Alireza Mehrtash, Amoon Jamzad, Amel Amalou, William M. Wells III, Tina Kapur, Jin Tae Kwak
Improving detection of prostate cancer foci via information fusion of MRI and temporal enhanced ultrasound. Int. J. Comput. Assist. Radiol. Surg. 15(7): 1215-1223 (2020) - [c22]Minh Nguyen Nhat To
Deep Learning Framework for Epithelium Density Estimation in Prostate Multi-Parametric Magnetic Resonance Imaging. ISBI 2020: 438-441 - [c21]Minh Nguyen Nhat To
Improving Dense Pixelwise Prediction of Epithelial Density Using Unsupervised Data Augmentation for Consistency Regularization. MICCAI (1) 2020: 572-581
2010 – 2019
- 2019
- [j13]Grant Haskins, Jochen Kruecker, Uwe Kruger, Sheng Xu, Peter A. Pinto, Bradford J. Wood
Learning deep similarity metric for 3D MR-TRUS image registration. Int. J. Comput. Assist. Radiol. Surg. 14(3): 417-425 (2019) - [j12]Alireza Sedghi
Deep neural maps for unsupervised visualization of high-grade cancer in prostate biopsies. Int. J. Comput. Assist. Radiol. Surg. 14(6): 1009-1016 (2019) - 2018
- [j11]Shekoofeh Azizi
Toward a real-time system for temporal enhanced ultrasound-guided prostate biopsy. Int. J. Comput. Assist. Radiol. Surg. 13(8): 1201-1209 (2018) - [j10]Yue Chen
MRI-Guided Robotically Assisted Focal Laser Ablation of the Prostate Using Canine Cadavers. IEEE Trans. Biomed. Eng. 65(7): 1434-1442 (2018) - [j9]Shekoofeh Azizi
Deep Recurrent Neural Networks for Prostate Cancer Detection: Analysis of Temporal Enhanced Ultrasound. IEEE Trans. Medical Imaging 37(12): 2695-2703 (2018) - [c20]Shekoofeh Azizi
Learning from Noisy Label Statistics: Detecting High Grade Prostate Cancer in Ultrasound Guided Biopsy. MICCAI (4) 2018: 21-29 - [c19]Abhishek Kolagunda, Scott Sorensen, Sherif Mehralivand
A Mixed Reality Guidance System for Robot Assisted Laparoscopic Radical Prostatectomy. OR 2.0/CARE/CLIP/ISIC@MICCAI 2018: 164-174 - [c18]Nathan Lay, Yohannes Tsehay, Yohan Sumathipala, Ruida Cheng, Sonia Gaur
A Decomposable Model for the Detection of Prostate Cancer in Multi-parametric MRI. MICCAI (2) 2018: 930-939 - [i1]Grant Haskins, Jochen Kruecker, Uwe Kruger, Sheng Xu, Peter A. Pinto, Bradford J. Wood, Pingkun Yan:
Learning Deep Similarity Metric for 3D MR-TRUS Registration. CoRR abs/1806.04548 (2018) - 2017
- [j8]Shekoofeh Azizi
Transfer learning from RF to B-mode temporal enhanced ultrasound features for prostate cancer detection. Int. J. Comput. Assist. Radiol. Surg. 12(7): 1111-1121 (2017) - [j7]Shekoofeh Azizi
Detection and grading of prostate cancer using temporal enhanced ultrasound: combining deep neural networks and tissue mimicking simulations. Int. J. Comput. Assist. Radiol. Surg. 12(8): 1293-1305 (2017) - [c17]Yohannes Tsehay, Nathan Lay, Xiaosong Wang
Biopsy-guided learning with deep convolutional neural networks for Prostate Cancer detection on multiparametric MRI. ISBI 2017: 642-645 - [c16]Yohannes K. Tsehay, Nathan S. Lay, Holger R. Roth
Convolutional neural network based deep-learning architecture for prostate cancer detection on multiparametric magnetic resonance images. Computer-Aided Diagnosis 2017: 1013405 - [c15]Reza Seifabadi, Sheng Xu, Fereshteh Aalamifar, Peter A. Pinto, Bradford J. Wood
Motorized fusion guided prostate biopsy: phantom study. Image-Guided Procedures 2017: 101352B - 2016
- [j6]Jin Tae Kwak
Correlation of magnetic resonance imaging with digital histopathology in prostate. Int. J. Comput. Assist. Radiol. Surg. 11(4): 657-666 (2016) - [j5]Shekoofeh Azizi
Detection of prostate cancer using temporal sequences of ultrasound data: a large clinical feasibility study. Int. J. Comput. Assist. Radiol. Surg. 11(6): 947-956 (2016) - [c14]Fereshteh Aalamifar, Reza Seifabadi, Marcelino Bernardo, Ayele H. Negussie
Ultrasound Tomosynthesis: A New Paradigm for Quantitative Imaging of the Prostate. MICCAI (1) 2016: 577-584 - [c13]Shekoofeh Azizi
Classifying Cancer Grades Using Temporal Ultrasound for Transrectal Prostate Biopsy. MICCAI (1) 2016: 653-661 - [c12]Sheng Xu, Harsh K. Agarwal, Marcelino Bernardo, Reza Seifabadi, Baris Turkbey, Ari Partanen, Ayele H. Negussie, Neil D. Glossop
An MRI guided system for prostate laser ablation with treatment planning and multi-planar temperature monitoring. Image-Guided Procedures 2016: 97861I - [c11]Reza Seifabadi, Sheng Xu, Peter A. Pinto, Bradford J. Wood
A motorized ultrasound system for MRI-ultrasound fusion guided prostatectomy. Image-Guided Procedures 2016: 97862H - 2015
- [j4]Farhad Imani, Bo Zhuang, Amir M. Tahmasebi, Jin Tae Kwak
Augmenting MRI-transrectal ultrasound-guided prostate biopsy with temporal ultrasound data: a clinical feasibility study. Int. J. Comput. Assist. Radiol. Surg. 10(6): 727-735 (2015) - [c10]Kevin Michael Boehm
Efficient Hilbert transform-based alternative to Tofts physiological models for representing MRI dynamic contrast-enhanced images in computer-aided diagnosis of prostate cancer. Computer-Aided Diagnosis 2015: 94140S - [c9]Shekoofeh Azizi
Ultrasound-Based Detection of Prostate Cancer Using Automatic Feature Selection with Deep Belief Networks. MICCAI (2) 2015: 70-77 - [c8]Jin Tae Kwak
Nucleus detection using gradient orientation information and linear least squares regression. Digital Pathology 2015: 94200N - 2014
- [c7]Nishant Uniyal, Farhad Imani, Amir M. Tahmasebi, Harsh K. Agarwal, Shyam Bharat, Pingkun Yan, Jochen Kruecker, Jin Tae Kwak
Ultrasound-Based Predication of Prostate Cancer in MRI-guided Biopsy. CLIP@MICCAI 2014: 142-150 - [c6]Jin Tae Kwak
A multiview boosting approach to tissue segmentation. Digital Pathology 2014: 90410R - 2013
- [j3]Helen Xu, Andras Lasso, Peter Guion, Axel Krieger, Aradhana Kaushal, Anurag K. Singh, Peter A. Pinto, Jonathan A. Coleman
Accuracy analysis in MRI-guided robotic prostate biopsy. Int. J. Comput. Assist. Radiol. Surg. 8(6): 937-944 (2013) - [j2]Yunsook Hong, John K. Visich, Peter A. Pinto, Basheer M. Khumawala:
Evaluation of mixed-model U-line operational designs. Int. Trans. Oper. Res. 20(6): 917-936 (2013) - [c5]Peter Liu, Shijun Wang, Baris Turkbey, Kinzya Grant, Peter A. Pinto, Peter L. Choyke, Bradford J. Wood
A prostate cancer computer-aided diagnosis system using multimodal magnetic resonance imaging and targeted biopsy labels. Computer-Aided Diagnosis 2013: 86701G - 2012
- [c4]Amir M. Tahmasebi, Reza Sharifi, Harsh K. Agarwal, Baris Turkbey, Marcelino Bernardo, Peter L. Choyke, Peter A. Pinto, Bradford J. Wood
A statistical model-based technique for accounting for prostate gland deformation in endorectal coil-based MR imaging. EMBC 2012: 5412-5415 - [c3]Shijun Wang, Peter Liu, Baris Turkbey, Peter L. Choyke, Peter A. Pinto, Ronald M. Summers:
Gaussian Process Inference for Estimating Pharmacokinetic Parameters of Dynamic Contrast-Enhanced MR Images. MICCAI (3) 2012: 582-589 - 2011
- [j1]Axel Krieger, Iulian Iordachita
An MRI-Compatible Robotic System With Hybrid Tracking for MRI-Guided Prostate Intervention. IEEE Trans. Biomed. Eng. 58(11): 3049-3060 (2011) - 2010
- [c2]Samuel Kadoury, Pingkun Yan
Realtime TRUS/MRI Fusion Targeted-Biopsy for Prostate Cancer: A Clinical Demonstration of Increased Positive Biopsy Rates. Prostate Cancer Imaging 2010: 52-62 - [c1]Sheng Xu, Baris Turkbey, Jochen Kruecker, Pingkun Yan
Multi-parametric MRI-pathologic correlation of prostate cancer using tracked biopsies. Image-Guided Procedures 2010: 76252R
Coauthor Index
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