AIMC Topic: Tomography, X-Ray Computed

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Automatic 3D liver segmentation based on deep learning and globally optimized surface evolution.

Physics in medicine and biology
The detection and delineation of the liver from abdominal 3D computed tomography (CT) images are fundamental tasks in computer-assisted liver surgery planning. However, automatic and accurate segmentation, especially liver detection, remains challeng...

Multi-atlas and unsupervised learning approach to perirectal space segmentation in CT images.

Australasian physical & engineering sciences in medicine
Perirectal space segmentation in computed tomography images aids in quantifying radiation dose received by healthy tissues and toxicity during the course of radiation therapy treatment of the prostate. Radiation dose normalised by tissue volume facil...

Adaptive Estimation of Active Contour Parameters Using Convolutional Neural Networks and Texture Analysis.

IEEE transactions on medical imaging
In this paper, we propose a generalization of the level set segmentation approach by supplying a novel method for adaptive estimation of active contour parameters. The presented segmentation method is fully automatic once the lesion has been detected...

Computerized tomography-based anatomic description of the porcine liver.

The Journal of surgical research
BACKGROUND: The knowledge of the anatomic features is imperative for successful modeling of the different surgical situations. This study aims to describe the anatomic features of the porcine using computerized tomography (CT) scan.

Artificial neural networks: Predicting head CT findings in elderly patients presenting with minor head injury after a fall.

The American journal of emergency medicine
OBJECTIVES: To construct an artificial neural network (ANN) model that can predict the presence of acute CT findings with both high sensitivity and high specificity when applied to the population of patients≄age 65years who have incurred minor head i...

Automatic segmentation of airway tree based on local intensity filter and machine learning technique in 3D chest CT volume.

International journal of computer assisted radiology and surgery
PURPOSE: Airway segmentation plays an important role in analyzing chest computed tomography (CT) volumes for computerized lung cancer detection, emphysema diagnosis and pre- and intra-operative bronchoscope navigation. However, obtaining a complete 3...

Machine learning-based 3-D geometry reconstruction and modeling of aortic valve deformation using 3-D computed tomography images.

International journal for numerical methods in biomedical engineering
To conduct a patient-specific computational modeling of the aortic valve, 3-D aortic valve anatomic geometries of an individual patient need to be reconstructed from clinical 3-D cardiac images. Currently, most of computational studies involve manual...

Computer-aided diagnosis system for lung nodules based on computed tomography using shape analysis, a genetic algorithm, and SVM.

Medical & biological engineering & computing
Lung cancer is the major cause of death among patients with cancer worldwide. This work is intended to develop a methodology for the diagnosis of lung nodules using images from the Image Database Consortium and Image Database Resource Initiative (LID...

Multilevel Contextual 3-D CNNs for False Positive Reduction in Pulmonary Nodule Detection.

IEEE transactions on bio-medical engineering
OBJECTIVE: False positive reduction is one of the most crucial components in an automated pulmonary nodule detection system, which plays an important role in lung cancer diagnosis and early treatment. The objective of this paper is to effectively add...

Pulmonary Nodule Detection Model Based on SVM and CT Image Feature-Level Fusion with Rough Sets.

BioMed research international
In order to improve the detection accuracy of pulmonary nodules in CT image, considering two problems of pulmonary nodules detection model, including unreasonable feature structure and nontightness of feature representation, a pulmonary nodules detec...