RATIONALE AND OBJECTIVES: Because it is imperative for understanding the performance of dual-energy computed tomography scanner to determine clinical diagnosis, we aimed to assess the accuracy of quantitative measurements using dual-energy computed t...
BACKGROUND: Whether compensatory lung growth occurs in adult humans is controversial. The aim of this study was to confirm compensatory lung growth by analyzing ipsilateral residual lung after lower lobectomy in living lung transplant donors with qua...
The Cleft palate-craniofacial journal : official publication of the American Cleft Palate-Craniofacial Association
Dec 14, 2017
OBJECTIVE: The objective of this study was to validate the proof of concept of a computer-simulated cranial distraction, demonstrating accurate shape and end volume.
OBJECTIVES: To examine the effect of incomplete, or total elimination of, projection data on computed tomography (CT) images subjected to statistical reconstruction and/or compressed sensing algorithms.
PURPOSE: Accurate identification of the gross tumor volume (GTV) in pancreatic adenocarcinoma is challenging. We sought to understand differences in GTV delineation using pancreatic computed tomography (CT) compared with magnetic resonance imaging (M...
We proposed an unsupervised hybrid method - Intelligent Word Embedding (IWE) that combines neural embedding method with a semantic dictionary mapping technique for creating a dense vector representation of unstructured radiology reports. We applied I...
Cardiovascular and interventional radiology
Nov 20, 2017
PURPOSE: To evaluate a commercially available robotic assistance device for computed tomography-guided diagnostic and therapeutic interventions, compared to regular, manually performed CT scan-guided interventions in terms of precision, exposure to r...
The 3D convolutional neural network (CNN) is able to make full use of the spatial 3D context information of lung nodules, and the multi-view strategy has been shown to be useful for improving the performance of 2D CNN in classifying lung nodules. In ...
In this paper, we introduce a simple, yet powerful pipeline for medical image segmentation that combines Fully Convolutional Networks (FCNs) with Fully Convolutional Residual Networks (FC-ResNets). We propose and examine a design that takes particula...
OBJECTIVE: To evaluate the diagnostic performance of machine-learning based quantitative texture analysis of CT images to differentiate small (≤ 4 cm) angiomyolipoma without visible fat (AMLwvf) from renal cell carcinoma (RCC).
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