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Prostatic Neoplasms

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Machine Segmentation of Pelvic Anatomy in MRI-Assisted Radiosurgery (MARS) for Prostate Cancer Brachytherapy.

International journal of radiation oncology, biology, physics Jul 4, 2020
PURPOSE: To investigate machine segmentation of pelvic anatomy in magnetic resonance imaging (MRI)-assisted radiosurgery (MARS) for prostate cancer using prostate brachytherapy MRIs acquired with different pulse sequences and image contrasts.
Urinary Bladder Entropy Urethra Magnetic Resonance Imaging, Interventional Rectum Brachytherapy Radiosurgery Seminal Vesicles Male Deep Learning Cohort Studies Image Processing, Computer-Assisted Prostatic Neoplasms Prostate Pelvis Humans Neural Networks, Computer Retrospective Studies
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Machine learning of diffraction image patterns for accurate classification of cells modeled with different nuclear sizes.

Journal of biophotonics Jul 3, 2020
Measurement of nuclear-to-cytoplasm (N:C) ratios plays an important role in detection of atypical and tumor cells. Yet, current clinical methods rely heavily on immunofluroescent staining and manual reading. To achieve the goal of rapid and label-fre...
Algorithms Male Humans Support Vector Machine Machine Learning Prostatic Neoplasms
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Machine learning for the identification of clinically significant prostate cancer on MRI: a meta-analysis.

European radiology Jun 30, 2020
OBJECTIVES: The aim of this study was to systematically review the literature and perform a meta-analysis of machine learning (ML) diagnostic accuracy studies focused on clinically significant prostate cancer (csPCa) identification on MRI.
Diagnosis, Computer-Assisted Humans ROC Curve Prostatectomy Algorithms Machine Learning Magnetic Resonance Imaging Area Under Curve Male Prevalence Prostatic Neoplasms Biopsy Reference Standards
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Bioinformatics analysis of the genes involved in the extension of prostate cancer to adjacent lymph nodes by supervised and unsupervised machine learning methods: The role of SPAG1 and PLEKHF2.

Genomics Jun 30, 2020
The present study aimed to identify the genes associated with the involvement of adjunct lymph nodes of patients with prostate cancer (PCa) and to provide valuable information for the identification of potential diagnostic biomarkers and pathological...
Supervised Machine Learning Datasets as Topic Antigens, Surface Lymphatic Metastasis Humans Vesicular Transport Proteins Cluster Analysis Male GTP-Binding Proteins Unsupervised Machine Learning Computational Biology Prostatic Neoplasms
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Using decision curve analysis to benchmark performance of a magnetic resonance imaging-based deep learning model for prostate cancer risk assessment.

European radiology Jun 26, 2020
OBJECTIVES: To benchmark the performance of a calibrated 3D convolutional neural network (CNN) applied to multiparametric MRI (mpMRI) for risk assessment of clinically significant prostate cancer (csPCa) using decision curve analysis (DCA).
Prostate-Specific Antigen Biopsy Benchmarking Humans Observer Variation Calibration Machine Learning Normal Distribution Algorithms Deep Learning Image Processing, Computer-Assisted Retrospective Studies Magnetic Resonance Imaging Male Prostatic Neoplasms Risk Assessment
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Re: Artificial Intelligence for Diagnosis and Grading of Prostate Cancer in Biopsies: A Population-Based, Diagnostic Study.

The Journal of urology Jun 26, 2020
Humans Biopsy Artificial Intelligence Male Prostatic Neoplasms
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Label-driven magnetic resonance imaging (MRI)-transrectal ultrasound (TRUS) registration using weakly supervised learning for MRI-guided prostate radiotherapy.

Physics in medicine and biology Jun 26, 2020
Registration and fusion of magnetic resonance imaging (MRI) and transrectal ultrasound (TRUS) of the prostate can provide guidance for prostate brachytherapy. However, accurate registration remains a challenging task due to the lack of ground truth r...
Ultrasonography Imaging, Three-Dimensional Magnetic Resonance Imaging Prostatic Neoplasms Humans Male Radiotherapy, Image-Guided Rectum Supervised Machine Learning Brachytherapy
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Superpixel-based deep convolutional neural networks and active contour model for automatic prostate segmentation on 3D MRI scans.

Medical & biological engineering & computing Jun 21, 2020
Automatic and reliable prostate segmentation is an essential prerequisite for assisting the diagnosis and treatment, such as guiding biopsy procedure and radiation therapy. Nonetheless, automatic segmentation is challenging due to the lack of clear p...
Prostatic Neoplasms Image Interpretation, Computer-Assisted Databases, Factual Male Deep Learning Latent Class Analysis Humans Imaging, Three-Dimensional Neural Networks, Computer Magnetic Resonance Imaging Algorithms Models, Statistical
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Histologic tissue components provide major cues for machine learning-based prostate cancer detection and grading on prostatectomy specimens.

Scientific reports Jun 18, 2020
Automatically detecting and grading cancerous regions on radical prostatectomy (RP) sections facilitates graphical and quantitative pathology reporting, potentially benefitting post-surgery prognosis, recurrence prediction, and treatment planning aft...
Prostatic Neoplasms Neoplasm Grading Neoplasm Recurrence, Local Prostatectomy Algorithms Male Diagnosis, Computer-Assisted Histological Techniques Humans Machine Learning
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Deep learning detection of prostate cancer recurrence with F-FACBC (fluciclovine, Axumin®) positron emission tomography.

European journal of nuclear medicine and molecular imaging Jun 17, 2020
PURPOSE: To evaluate the performance of deep learning (DL) classifiers in discriminating normal and abnormal F-FACBC (fluciclovine, Axumin®) PET scans based on the presence of tumor recurrence and/or metastases in patients with prostate cancer (PC) a...
Prostatic Neoplasms Tomography, X-Ray Computed Carboxylic Acids Male Neoplasm Recurrence, Local Humans Deep Learning Cyclobutanes Positron-Emission Tomography Positron Emission Tomography Computed Tomography
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