AIMC Journal:
Medical image analysis

Showing 641 to 650 of 699 articles

A machine-learning graph-based approach for 3D segmentation of Bruch's membrane opening from glaucomatous SD-OCT volumes.

Medical image analysis May 6, 2017
Bruch's membrane opening-minimum rim width (BMO-MRW) is a recently proposed structural parameter which estimates the remaining nerve fiber bundles in the retina and is superior to other conventional structural parameters for diagnosing glaucoma. Meas...
Humans Tomography, Optical Coherence Optic Disk Bruch Membrane Machine Learning Imaging, Three-Dimensional Glaucoma
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Deep image mining for diabetic retinopathy screening.

Medical image analysis Apr 28, 2017
Deep learning is quickly becoming the leading methodology for medical image analysis. Given a large medical archive, where each image is associated with a diagnosis, efficient pathology detectors or classifiers can be trained with virtually no expert...
Humans Diabetic Retinopathy Artifacts Machine Learning Algorithms Data Mining Image Interpretation, Computer-Assisted Retina
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Convolutional neural network regression for short-axis left ventricle segmentation in cardiac cine MR sequences.

Medical image analysis Apr 12, 2017
Automated left ventricular (LV) segmentation is crucial for efficient quantification of cardiac function and morphology to aid subsequent management of cardiac pathologies. In this paper, we parameterize the complete (all short axis slices and phases...
Image Interpretation, Computer-Assisted Magnetic Resonance Imaging, Cine Regression Analysis Heart Ventricles Humans Neural Networks, Computer Machine Learning Reproducibility of Results
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A deep learning approach for the analysis of masses in mammograms with minimal user intervention.

Medical image analysis Jan 28, 2017
We present an integrated methodology for detecting, segmenting and classifying breast masses from mammograms with minimal user intervention. This is a long standing problem due to low signal-to-noise ratio in the visualisation of breast masses, combi...
Mammography Bayes Theorem Machine Learning Breast Neoplasms Female Radiographic Image Interpretation, Computer-Assisted Humans Sensitivity and Specificity Breast
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Deep ensemble learning of sparse regression models for brain disease diagnosis.

Medical image analysis Jan 24, 2017
Recent studies on brain imaging analysis witnessed the core roles of machine learning techniques in computer-assisted intervention for brain disease diagnosis. Of various machine-learning techniques, sparse regression models have proved their effecti...
Alzheimer Disease Magnetic Resonance Imaging Regression Analysis Reproducibility of Results Aged Male Cognitive Dysfunction Sensitivity and Specificity Prognosis Clinical Decision-Making Female Machine Learning Brain Humans
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Accurate and interpretable classification of microspectroscopy pixels using artificial neural networks.

Medical image analysis Jan 6, 2017
This paper addresses the problem of classifying materials from microspectroscopy at a pixel level. The challenges lie in identifying discriminatory spectral features and obtaining accurate and interpretable models relating spectra and class labels. W...
Neural Networks, Computer Algorithms Spectrum Analysis Reproducibility of Results Sensitivity and Specificity
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DCAN: Deep contour-aware networks for object instance segmentation from histology images.

Medical image analysis Nov 16, 2016
In histopathological image analysis, the morphology of histological structures, such as glands and nuclei, has been routinely adopted by pathologists to assess the malignancy degree of adenocarcinomas. Accurate detection and segmentation of these obj...
Histological Techniques Machine Learning Humans Colorectal Neoplasms
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Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation.

Medical image analysis Oct 29, 2016
We propose a dual pathway, 11-layers deep, three-dimensional Convolutional Neural Network for the challenging task of brain lesion segmentation. The devised architecture is the result of an in-depth analysis of the limitations of current networks pro...
Brain Neoplasms Brain Ischemia Humans Brain Injuries, Traumatic Reproducibility of Results Brain Neural Networks, Computer Sensitivity and Specificity
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Deep learning for automated skeletal bone age assessment in X-ray images.

Medical image analysis Oct 29, 2016
Skeletal bone age assessment is a common clinical practice to investigate endocrinology, genetic and growth disorders in children. It is generally performed by radiological examination of the left hand by using either the Greulich and Pyle (G&P) meth...
Reproducibility of Results Child Humans Age Determination by Skeleton Male Adolescent Radiography Neural Networks, Computer Infant Bone and Bones Child, Preschool Machine Learning Female
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Unsupervised boundary delineation of spinal neural foramina using a multi-feature and adaptive spectral segmentation.

Medical image analysis Oct 29, 2016
As a common disease in the elderly, neural foramina stenosis (NFS) brings a significantly negative impact on the quality of life due to its symptoms including pain, disability, fall risk and depression. Accurate boundary delineation is essential to t...
Spinal Stenosis Spinal Canal Algorithms Magnetic Resonance Imaging Unsupervised Machine Learning Humans
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