A Deep Learning Approach to Diagnostic Classification of Prostate Cancer Using Pathology–Radiology Fusion
出版年份 2021 全文链接
标题
A Deep Learning Approach to Diagnostic Classification of Prostate Cancer Using Pathology–Radiology Fusion
作者
关键词
-
出版物
JOURNAL OF MAGNETIC RESONANCE IMAGING
Volume -, Issue -, Pages -
出版商
Wiley
发表日期
2021-03-15
DOI
10.1002/jmri.27599
参考文献
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注意:仅列出部分参考文献,下载原文获取全部文献信息。- A robust and interpretable end-to-end deep learning model for cytometry data
- (2020) Zicheng Hu et al. PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
- Prostate cancer classification with multiparametric MRI transfer learning model
- (2019) Yixuan Yuan et al. MEDICAL PHYSICS
- Joint Prostate Cancer Detection and Gleason Score Prediction in mp-MRI via FocalNet
- (2019) Ruiming Cao et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- Prostate Imaging-Reporting and Data System Steering Committee: PI-RADS v2 Status Update and Future Directions
- (2018) Anwar R. Padhani et al. EUROPEAN UROLOGY
- DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs
- (2018) Liang-Chieh Chen et al. IEEE TRANSACTIONS ON PATTERN ANALYSIS AND MACHINE INTELLIGENCE
- Global cancer incidence in older adults, 2012 and 2035: A population-based study
- (2018) Sophie Pilleron et al. INTERNATIONAL JOURNAL OF CANCER
- Deep Convolutional Neural Networks Enable Discrimination of Heterogeneous Digital Pathology Images
- (2018) Pegah Khosravi et al. EBioMedicine
- Diagnosis of transition zone prostate cancer using T2-weighted (T2W) MRI: comparison of subjective features and quantitative shape analysis
- (2018) Satheesh Krishna et al. EUROPEAN RADIOLOGY
- Development and validation of a novel automated Gleason grade and molecular profile that define a highly predictive prostate cancer progression algorithm-based test
- (2018) Michael J. Donovan et al. PROSTATE CANCER AND PROSTATIC DISEASES
- A survey on deep learning in medical image analysis
- (2017) Geert Litjens et al. MEDICAL IMAGE ANALYSIS
- Searching for prostate cancer by fully automated magnetic resonance imaging classification: deep learning versus non-deep learning
- (2017) Xinggang Wang et al. Scientific Reports
- Preoperative Evaluation of Prostate Cancer Aggressiveness: Using ADC and ADC Ratio in Determining Gleason Score
- (2016) Sungmin Woo et al. AMERICAN JOURNAL OF ROENTGENOLOGY
- Optimizing safety and accuracy of prostate biopsy
- (2016) Tonye A. Jones et al. CURRENT OPINION IN UROLOGY
- 10-Year Outcomes after Monitoring, Surgery, or Radiotherapy for Localized Prostate Cancer
- (2016) Freddie C. Hamdy et al. NEW ENGLAND JOURNAL OF MEDICINE
- The 2014 International Society of Urological Pathology (ISUP) Consensus Conference on Gleason Grading of Prostatic Carcinoma
- (2015) Jonathan I. Epstein et al. AMERICAN JOURNAL OF SURGICAL PATHOLOGY
- Updated prostate imaging reporting and data system (PIRADS v2) recommendations for the detection of clinically significant prostate cancer using multiparametric MRI: critical evaluation using whole-mount pathology as standard of reference
- (2015) H. A. Vargas et al. EUROPEAN RADIOLOGY
- XSEDE: Accelerating Scientific Discovery
- (2014) John Towns et al. COMPUTING IN SCIENCE & ENGINEERING
- Computer-Aided Detection of Prostate Cancer in MRI
- (2014) Geert Litjens et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- The Cancer Imaging Archive (TCIA): Maintaining and Operating a Public Information Repository
- (2013) Kenneth Clark et al. JOURNAL OF DIGITAL IMAGING
- Validation of the European Society of Urogenital Radiology Scoring System for Prostate Cancer Diagnosis on Multiparametric Magnetic Resonance Imaging in a Cohort of Repeat Biopsy Patients
- (2012) Daniel Portalez et al. EUROPEAN UROLOGY
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