AIMC Topic: Prostate
Clear Filters Showing 451 to 460 of 617 articles
Deep dense multi-path neural network for prostate segmentation in magnetic resonance imaging.
International journal of computer assisted radiology and surgery
Aug 7, 2018
PURPOSE: We propose an approach of 3D convolutional neural network to segment the prostate in MR images.
Radiomic Machine Learning for Characterization of Prostate Lesions with MRI: Comparison to ADC Values.
Radiology
Jul 31, 2018
Purpose To compare biparametric contrast-free radiomic machine learning (RML), mean apparent diffusion coefficient (ADC), and radiologist assessment for characterization of prostate lesions detected during prospective MRI interpretation. Materials an...
Response to Skarecky re: Development of a Patient-Based Model for Estimating Operative Times for Robot-Assisted Radical Prostatectomy by Huben et al.
Journal of endourology
Jul 26, 2018
Re: The Impact of Implementation of the European Association of Urology Guidelines Panel Recommendations on Reporting and Grading Complications on Perioperative outcomes after Robot-assisted Radical Prostatectomy.
European urology
Jul 20, 2018
Editorial Comment on: Development of a Patient-Based Model for Estimating Operative Times for Robot-Assisted Radical Prostatectomy by Huben et al.
Journal of endourology
Jul 9, 2018
Weakly-supervised convolutional neural networks for multimodal image registration.
Medical image analysis
Jul 4, 2018
One of the fundamental challenges in supervised learning for multimodal image registration is the lack of ground-truth for voxel-level spatial correspondence. This work describes a method to infer voxel-level transformation from higher-level correspo...
Deep Recurrent Neural Networks for Prostate Cancer Detection: Analysis of Temporal Enhanced Ultrasound.
IEEE transactions on medical imaging
Jun 25, 2018
Temporal enhanced ultrasound (TeUS), comprising the analysis of variations in backscattered signals from a tissue over a sequence of ultrasound frames, has been previously proposed as a new paradigm for tissue characterization. In this paper, we prop...
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