AIMC Topic: X-Rays

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An Attention-Guided Deep Neural Network for Annotating Abnormalities in Chest X-ray Images: Visualization of Network Decision Basis.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
Despite the potential of deep convolutional neural networks for classification of thorax diseases from chest X-ray images, this task is still challenging as it is categorized as a weakly supervised learning problem, and deep neural networks in genera...
Neural Networks, Computer Algorithms Attention Thorax X-Rays
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Lung Region Segmentation in Chest X-Ray Images using Deep Convolutional Neural Networks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
Lung cancer is, by far, the leading cause of cancer death in the world. Tools for automated medical imaging analysis development of a Computer-Aided Diagnosis method comprises several tasks. In general, the first one is the segmentation of region of ...
Diagnosis, Computer-Assisted Thorax X-Rays Neural Networks, Computer Lung
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Dense-Unet: a light model for lung fields segmentation in Chest X-Ray images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
Automatic and accurate lung segmentation in chest X-ray (CXR) images is fundamental for computer-aided diagnosis systems since the lung is the region of interest in many diseases and also it can reveal useful information by its contours. While deep l...
X-Rays Diagnosis, Computer-Assisted Thorax Neural Networks, Computer Lung
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Multi-View Ensemble Convolutional Neural Network to Improve Classification of Pneumonia in Low Contrast Chest X-Ray Images.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2020
Pneumonia is one of the leading causes of childhood mortality worldwide. Chest x-ray (CXR) can aid the diagnosis of pneumonia, but in the case of low contrast images, it is important to include computational tools to aid specialists. Deep learning is...
Humans Neural Networks, Computer Pneumonia Thorax X-Rays Deep Learning Child
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An Efficient Method to Predict Pneumonia from Chest X-Rays Using Deep Learning Approach.

Studies in health technology and informatics Jun 26, 2020
Pneumonia is a severe health problem causing millions of deaths every year. The aim of this study was to develop an advanced deep learning-based architecture to detect pneumonia using chest X-ray images. We utilized a convolutional neural network (CN...
Deep Learning Pneumonia Humans Neural Networks, Computer Radiographic Image Interpretation, Computer-Assisted X-Rays
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Skeletal bone age assessments for young children based on regression convolutional neural networks.

Mathematical biosciences and engineering : MBE Jul 12, 2019
Pediatricians and pediatric endocrinologists utilize Bone Age Assessment (BAA) for in-vestigations pertaining to genetic disorders, hormonal complications and abnormalities in the skeletal system maturity of children. Conventional methods dating back...
Observer Variation Pattern Recognition, Automated Age Determination by Skeleton Carpal Bones X-Rays Regression Analysis Data Interpretation, Statistical Child Image Processing, Computer-Assisted Neural Networks, Computer Algorithms Humans Male Infant Adolescent Child, Preschool China Reproducibility of Results Young Adult Female Infant, Newborn
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Model-free Cardiorespiratory Motion Prediction from X-ray Angiography Sequence with LSTM Network.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
We present a novel model-free approach for cardiorespiratory motion prediction from X-ray angiography time series based on Long Short-Term Memory Recurrent Neural Networks (LSTM-RNN). Cardiorespiratory motion prediction is defined as a problem of est...
X-Rays Humans Neural Networks, Computer Motion Angiography Forecasting
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Deep Feature Learning from a Hospital-Scale Chest X-ray Dataset with Application to TB Detection on a Small-Scale Dataset.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
The use of ImageNet pre-trained networks is becoming widespread in the medical imaging community. It enables training on small datasets, commonly available in medical imaging tasks. The recent emergence of a large Chest X-ray dataset opened the possi...
Neural Networks, Computer Deep Learning Humans X-Rays Tuberculosis Radiography, Thoracic
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Assessment of an ensemble of machine learning models toward abnormality detection in chest radiographs.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference Jul 1, 2019
Respiratory diseases account for a significant proportion of deaths and disabilities across the world. Chest X-ray (CXR) analysis remains a common diagnostic imaging modality for confirming intra-thoracic cardiopulmonary abnormalities. However, there...
Respiratory Tract Diseases X-Rays Humans Neural Networks, Computer Image Processing, Computer-Assisted Radiography, Thoracic Machine Learning Algorithms
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[Automatic Segmentation of Anatomical Areas in X-ray Images Based on Fully Convolutional Networks].

Zhongguo yi liao qi xie za zhi = Chinese journal of medical instrumentation May 30, 2019
OBJECTIVE: Medical image segmentation is a key step in medical image processing. An architecture of fully convolutional networks was proposed to realize automatic segmentation of anatomical areas in X-ray images.
Image Processing, Computer-Assisted X-Rays Neural Networks, Computer Algorithms
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