AIMC Topic: Image Interpretation, Computer-Assisted

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All eyes are on AI.

Nature biomedical engineering Mar 1, 2018
Image Interpretation, Computer-Assisted Algorithms Retinal Diseases Cardiovascular Diseases Retina Humans Artificial Intelligence
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Adversarial Stain Transfer for Histopathology Image Analysis.

IEEE transactions on medical imaging Mar 1, 2018
It is generally recognized that color information is central to the automatic and visual analysis of histopathology tissue slides. In practice, pathologists rely on color, which reflects the presence of specific tissue components, to establish a diag...
Staining and Labeling Image Interpretation, Computer-Assisted Histocytochemistry Machine Learning Humans Neoplasms Image Processing, Computer-Assisted
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Role of Big Data and Machine Learning in Diagnostic Decision Support in Radiology.

Journal of the American College of Radiology : JACR Mar 1, 2018
The field of diagnostic decision support in radiology is undergoing rapid transformation with the availability of large amounts of patient data and the development of new artificial intelligence methods of machine learning such as deep learning. They...
Image Interpretation, Computer-Assisted Deep Learning Big Data Radiology Humans Machine Learning Decision Support Techniques
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Artificial intelligence in medicine: current trends and future possibilities.

The British journal of general practice : the journal of the Royal College of General Practitioners Mar 1, 2018
Humans Artificial Intelligence Image Interpretation, Computer-Assisted Evidence-Based Medicine Machine Learning Decision Making, Computer-Assisted Forecasting Clinical Decision-Making
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Deep learning for biology.

Nature Feb 22, 2018
Image Interpretation, Computer-Assisted Rodentia Robotics Diagnostic Imaging Plants Biology Microscopy Quality Control Drug Discovery Genomics Humans Polymorphism, Single Nucleotide Neural Networks, Computer Electronic Health Records Machine Learning Animals Software
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Use of Fetal Magnetic Resonance Image Analysis and Machine Learning to Predict the Need for Postnatal Cerebrospinal Fluid Diversion in Fetal Ventriculomegaly.

JAMA pediatrics Feb 1, 2018
IMPORTANCE: Which children with fetal ventriculomegaly, or enlargement of the cerebral ventricles in utero, will develop hydrocephalus requiring treatment after birth is unclear.
Machine Learning Retrospective Studies Pregnancy Humans Magnetic Resonance Imaging Predictive Value of Tests Hydrocephalus Female Infant, Newborn Case-Control Studies Image Interpretation, Computer-Assisted Prenatal Diagnosis
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Femur segmentation in DXA imaging using a machine learning decision tree.

Journal of X-ray science and technology Jan 1, 2018
BACKGROUND: Accurate measurement of bone mineral density (BMD) in dual-energy X-ray absorptiometry (DXA) is essential for proper diagnosis of osteoporosis. Calculation of BMD requires precise bone segmentation and subtraction of soft tissue absorptio...
Image Interpretation, Computer-Assisted Absorptiometry, Photon Femur Machine Learning Humans Osteoporosis Decision Trees
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Deep Learning Role in Early Diagnosis of Prostate Cancer.

Technology in cancer research & treatment Jan 1, 2018
The objective of this work is to develop a computer-aided diagnostic system for early diagnosis of prostate cancer. The presented system integrates both clinical biomarkers (prostate-specific antigen) and extracted features from diffusion-weighted ma...
Image Interpretation, Computer-Assisted Diffusion Magnetic Resonance Imaging Sensitivity and Specificity ROC Curve Male Early Detection of Cancer Humans Deep Learning Prostatic Neoplasms Algorithms Reproducibility of Results
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Diabetic macular edema grading in retinal images using vector quantization and semi-supervised learning.

Technology and health care : official journal of the European Society for Engineering and Medicine Jan 1, 2018
BACKGROUND: Diabetic macular edema (DME) is one of the severe complication of diabetic retinopathy causing severe vision loss and leads to blindness in severe cases if left untreated.
Supervised Machine Learning Macular Edema Image Interpretation, Computer-Assisted Exudates and Transudates Diabetic Retinopathy Sensitivity and Specificity Severity of Illness Index Humans
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Retinal Lesion Detection With Deep Learning Using Image Patches.

Investigative ophthalmology & visual science Jan 1, 2018
PURPOSE: To develop an automated method of localizing and discerning multiple types of findings in retinal images using a limited set of training data without hard-coded feature extraction as a step toward generalizing these methods to rare disease d...
Humans Neural Networks, Computer Exudates and Transudates Retinal Diseases ROC Curve Probability Image Interpretation, Computer-Assisted Machine Learning Algorithms Reproducibility of Results
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