AMIA ... Annual Symposium proceedings. AMIA Symposium
Dec 5, 2018
We propose a scalable computerized approach for large-scale inference of Liver Imaging Reporting and Data System (LI-RADS) final assessment categories in narrative ultrasound (US) reports. Although our model was trained on reports created using a LI-...
Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract
Nov 7, 2018
BACKGROUND: The objective of this study was to evaluate the learning curve effect on the safety and feasibility of robot-assisted liver resection (RALR).
Automatic liver tumor segmentation would have a big impact on liver therapy planning procedures and follow-up assessment, thanks to standardization and incorporation of full volumetric information. In this work, we develop a fully automatic method fo...
Journal of visualized experiments : JoVE
Oct 10, 2018
Intra-arterial therapies are the standard of care for patients with hepatocellular carcinoma who cannot undergo surgical resection. The objective of this study was to develop a method to predict response to intra-arterial treatment prior to intervent...
The automated segmentation of liver and tumor from CT images is of great importance in medical diagnoses and clinical treatment. However, accurate and automatic segmentation of liver and tumor is generally complicated due to the complex anatomical st...
PURPOSE: The purpose of this study was the evaluation of anthropomorphic model observers trained with neural networks for the prediction of a human observer's performance.
Journal of gastrointestinal surgery : official journal of the Society for Surgery of the Alimentary Tract
Jun 18, 2018
BACKGROUND: The essential issue of internal validity has not been adequately addressed in prediction models such as artificial neural network (ANN), support vector machine (SVM), Gaussian process regression (GPR), and multiple linear regression (MLR)...
Liver cancer is one of the leading causes of cancer death. To assist doctors in hepatocellular carcinoma diagnosis and treatment planning, an accurate and automatic liver and tumor segmentation method is highly demanded in the clinical practice. Rece...
Journal of vascular and interventional radiology : JVIR
Mar 14, 2018
PURPOSE: To use magnetic resonance (MR) imaging and clinical patient data to create an artificial intelligence (AI) framework for the prediction of therapeutic outcomes of transarterial chemoembolization by applying machine learning (ML) techniques.
Medical & biological engineering & computing
Mar 10, 2018
Radiological longitudinal follow-up of tumors in CT scans is essential for disease assessment and liver tumor therapy. Currently, most tumor size measurements follow the RECIST guidelines, which can be off by as much as 50%. True volumetric measureme...