AIMC Topic: Radiographic Image Enhancement
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SD-CNN: A shallow-deep CNN for improved breast cancer diagnosis.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Sep 22, 2018
Breast cancer is the second leading cause of cancer death among women worldwide. Nevertheless, it is also one of the most treatable malignances if detected early. Screening for breast cancer with full field digital mammography (FFDM) has been widely ...
Development and Validation of a Deep Learning System for Staging Liver Fibrosis by Using Contrast Agent-enhanced CT Images in the Liver.
Radiology
Sep 4, 2018
Purpose To develop and validate a deep learning system (DLS) for staging liver fibrosis by using CT images in the liver. Materials and Methods DLS for CT-based staging of liver fibrosis was created by using a development data set that included portal...
Small airway segmentation in thoracic computed tomography scans: a machine learning approach.
Physics in medicine and biology
Aug 6, 2018
Small airway obstruction is a main cause for chronic obstructive pulmonary disease (COPD). We propose a novel method based on machine learning to extract the airway system from a thoracic computed tomography (CT) scan. The emphasis of the proposed me...
A fully integrated computer-aided diagnosis system for digital X-ray mammograms via deep learning detection, segmentation, and classification.
International journal of medical informatics
Jun 18, 2018
A computer-aided diagnosis (CAD) system requires detection, segmentation, and classification in one framework to assist radiologists efficiently in an accurate diagnosis. In this paper, a completely integrated CAD system is proposed to screen digital...
Small lung nodules detection based on local variance analysis and probabilistic neural network.
Computer methods and programs in biomedicine
Apr 28, 2018
BACKGROUND AND OBJECTIVE: In medical examinations doctors use various techniques in order to provide to the patients an accurate analysis of their actual state of health. One of the commonly used methodologies is the x-ray screening. This examination...
X-Rays
Radiographic Image Enhancement
Medical Errors
Solitary Pulmonary Nodule
Radiographic Image Interpretation, Computer-Assisted
Neural Networks, Computer
Carcinoma
Probability
Algorithms
Pattern Recognition, Automated
Humans
False Positive Reactions
Lung
Image Processing, Computer-Assisted
Databases, Factual
Lung Neoplasms
Reproducibility of Results
Sensitivity and Specificity
A Novel Multiscale Gaussian-Matched Filter Using Neural Networks for the Segmentation of X-Ray Coronary Angiograms.
Journal of healthcare engineering
Apr 18, 2018
The accurate and efficient segmentation of coronary arteries in X-ray angiograms represents an essential task for computer-aided diagnosis. This paper presents a new multiscale Gaussian-matched filter (MGMF) based on artificial neural networks. The p...
Automated estimation of image quality for coronary computed tomographic angiography using machine learning.
European radiology
Mar 23, 2018
OBJECTIVES: Our goal was to evaluate the efficacy of a fully automated method for assessing the image quality (IQ) of coronary computed tomography angiography (CCTA).
A robotic C-arm cone beam CT system for image-guided proton therapy: design and performance.
The British journal of radiology
Oct 9, 2017
OBJECTIVE: A ceiling-mounted robotic C-arm cone beam CT (CBCT) system was developed for use with a 190° proton gantry system and a 6-degree-of-freedom robotic patient positioner. We report on the mechanical design, system accuracy, image quality, ima...
Artificial intelligence for analyzing orthopedic trauma radiographs.
Acta orthopaedica
Jul 6, 2017
Background and purpose - Recent advances in artificial intelligence (deep learning) have shown remarkable performance in classifying non-medical images, and the technology is believed to be the next technological revolution. So far it has never been ...
Tomographic image reconstruction via estimation of sparse unidirectional gradients.
Computers in biology and medicine
Dec 21, 2016
Since computed tomography (CT) was developed over 35 years ago, new mathematical ideas and computational algorithms have been continuingly elaborated to improve the quality of reconstructed images. In recent years, a considerable effort can be notice...
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