Prediction of Microvascular Invasion of Hepatocellular Carcinoma Based on Preoperative Diffusion-Weighted MR Using Deep Learning
Published 2020 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
Prediction of Microvascular Invasion of Hepatocellular Carcinoma Based on Preoperative Diffusion-Weighted MR Using Deep Learning
Authors
Keywords
-
Journal
ACADEMIC RADIOLOGY
Volume -, Issue -, Pages -
Publisher
Elsevier BV
Online
2020-12-07
DOI
10.1016/j.acra.2020.11.014
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Preoperative radiomics nomogram for microvascular invasion prediction in hepatocellular carcinoma using contrast-enhanced CT
- (2019) Xiaohong Ma et al. EUROPEAN RADIOLOGY
- Preoperative prediction of microvascular invasion in hepatocellular cancer: a radiomics model using Gd-EOB-DTPA-enhanced MRI
- (2019) Shi-Ting Feng et al. EUROPEAN RADIOLOGY
- Deep learning with convolutional neural network in radiology
- (2018) Koichiro Yasaka et al. JAPANESE JOURNAL OF RADIOLOGY
- Deep Learning with Convolutional Neural Network for Differentiation of Liver Masses at Dynamic Contrast-enhanced CT: A Preliminary Study
- (2018) Koichiro Yasaka et al. RADIOLOGY
- Liver Fibrosis: Deep Convolutional Neural Network for Staging by Using Gadoxetic Acid–enhanced Hepatobiliary Phase MR Images
- (2018) Koichiro Yasaka et al. RADIOLOGY
- Assessment of Microvascular Invasion of Hepatocellular Carcinoma with Diffusion Kurtosis Imaging
- (2018) Wen-Tao Wang et al. RADIOLOGY
- Deep learning with convolutional neural network in radiology
- (2018) Koichiro Yasaka et al. Japanese Journal of Radiology
- A radiomics nomogram for preoperative prediction of microvascular invasion risk in hepatitis B virus-related hepatocellular carcinoma
- (2018) Jie Peng et al. Diagnostic and Interventional Radiology
- Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries
- (2018) Freddie Bray et al. CA-A CANCER JOURNAL FOR CLINICIANS
- A survey on deep learning in medical image analysis
- (2017) Geert Litjens et al. MEDICAL IMAGE ANALYSIS
- Microvascular invasion in hepatocellular carcinoma
- (2016) Emre Unal et al. Diagnostic and Interventional Radiology
- A pre-operative clinical model to predict microvascular invasion and long-term outcome after resection of hepatocellular cancer: The Australian experience
- (2016) S.M. Schlichtemeier et al. EJSO
- Guest Editorial Deep Learning in Medical Imaging: Overview and Future Promise of an Exciting New Technique
- (2016) Hayit Greenspan et al. IEEE TRANSACTIONS ON MEDICAL IMAGING
- Value of MR histogram analyses for prediction of microvascular invasion of hepatocellular carcinoma
- (2016) Ya-Qin Huang et al. MEDICINE
- Can Current Preoperative Imaging Be Used to Detect Microvascular Invasion of Hepatocellular Carcinoma?
- (2016) Matteo Renzulli et al. RADIOLOGY
- Radiomics: Images Are More than Pictures, They Are Data
- (2016) Robert J. Gillies et al. RADIOLOGY
- Microvascular invasion in hepatocellular carcinoma
- (2016) Emre Unal et al. Diagnostic and Interventional Radiology
- Prediction of Microvascular Invasion of Hepatocellular Carcinoma: Preoperative CT and Histopathologic Correlation
- (2014) Chen-Te Chou et al. AMERICAN JOURNAL OF ROENTGENOLOGY
- Influence of image registration on apparent diffusion coefficient images computed from free-breathing diffusion MR images of the abdomen
- (2014) Jean-Marie Guyader et al. JOURNAL OF MAGNETIC RESONANCE IMAGING
- New scoring system for prediction of microvascular invasion in patients with hepatocellular carcinoma
- (2014) Ken Shirabe et al. LIVER INTERNATIONAL
- Hierarchical feature representation and multimodal fusion with deep learning for AD/MCI diagnosis
- (2014) Heung-Il Suk et al. NEUROIMAGE
- CT and MR Imaging Diagnosis and Staging of Hepatocellular Carcinoma: Part II. Extracellular Agents, Hepatobiliary Agents, and Ancillary Imaging Features
- (2014) Jin-Young Choi et al. RADIOLOGY
- Preoperative predictors of microvascular invasion in multinodular hepatocellular carcinoma
- (2013) W.-C. Zhao et al. EJSO
- A Systematic Review of Microvascular Invasion in Hepatocellular Carcinoma: Diagnostic and Prognostic Variability
- (2012) Manuel Rodríguez-Perálvarez et al. ANNALS OF SURGICAL ONCOLOGY
- Systematic review of outcomes of liver resection for early hepatocellular carcinoma within the Milan criteria
- (2012) K.-C. Lim et al. BRITISH JOURNAL OF SURGERY
- Preoperative prediction of the microvascular invasion of hepatocellular carcinoma with diffusion-weighted imaging
- (2012) Young Joo Suh et al. LIVER TRANSPLANTATION
- Microvascular Invasion Is a Better Predictor of Tumor Recurrence and Overall Survival Following Surgical Resection for Hepatocellular Carcinoma Compared to the Milan Criteria
- (2011) Kheng-Choon Lim et al. ANNALS OF SURGERY
- A non-smooth tumor margin in the hepatobiliary phase of gadoxetic acid disodium (Gd-EOB-DTPA)-enhanced magnetic resonance imaging predicts microscopic portal vein invasion, intrahepatic metastasis, and early recurrence after hepatectomy in patients with h
- (2011) Shun-ichi Ariizumi et al. Journal of Hepato-Biliary-Pancreatic Sciences
- Prediction of microvascular invasion of hepatocellular carcinoma: Usefulness of peritumoral hypointensity seen on gadoxetate disodium-enhanced hepatobiliary phase images
- (2011) Kyung Ah Kim et al. JOURNAL OF MAGNETIC RESONANCE IMAGING
- Preoperative prediction of hepatocellular carcinoma tumour grade and micro-vascular invasion by means of artificial neural network: A pilot study
- (2010) Alessandro Cucchetti et al. JOURNAL OF HEPATOLOGY
- Alpha-fetoprotein and tumour size are associated with microvascular invasion in explanted livers of patients undergoing transplantation with hepatocellular carcinoma
- (2010) Patrick P. McHugh et al. HPB
- Diffusion-weighted MR Imaging of the Liver
- (2009) Bachir Taouli et al. RADIOLOGY
Publish scientific posters with Peeref
Peeref publishes scientific posters from all research disciplines. Our Diamond Open Access policy means free access to content and no publication fees for authors.
Learn MoreAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started