AIMC Topic: Diagnostic Imaging

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Classification of Medical Images in the Biomedical Literature by Jointly Using Deep and Handcrafted Visual Features.

IEEE journal of biomedical and health informatics Nov 20, 2017
The classification of medical images and illustrations from the biomedical literature is important for automated literature review, retrieval, and mining. Although deep learning is effective for large-scale image classification, it may not be the opt...
Deep Learning Image Processing, Computer-Assisted Diagnostic Imaging Humans Algorithms
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Radiomics and radiogenomics in lung cancer: A review for the clinician.

Lung cancer (Amsterdam, Netherlands) Nov 8, 2017
Lung cancer is responsible for a large proportion of cancer-related deaths across the globe, with delayed detection being perhaps the most significant factor for its high mortality rate. Though the National Lung Screening Trial argues for screening o...
Diagnostic Imaging Reference Standards Lung Neoplasms Early Detection of Cancer Tomography, X-Ray Computed Algorithms Lung Humans Prognosis Animals Image Processing, Computer-Assisted Software
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Machine Learning for Predicting Patient Wait Times and Appointment Delays.

Journal of the American College of Radiology : JACR Oct 24, 2017
Being able to accurately predict waiting times and scheduled appointment delays can increase patient satisfaction and enable staff members to more accurately assess and respond to patient flow. In this work, the authors studied the applicability of m...
Patient Satisfaction Radiology Information Systems Workflow Waiting Lists Machine Learning Algorithms Humans Retrospective Studies Predictive Value of Tests Diagnostic Imaging
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Towards machine learned quality control: A benchmark for sharpness quantification in digital pathology.

Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society Sep 25, 2017
Pathology is on the verge of a profound change from an analog and qualitative to a digital and quantitative discipline. This change is mostly driven by the high-throughput scanning of microscope slides in modern pathology departments, reaching tens o...
Neural Networks, Computer Machine Learning Diagnostic Imaging Image Enhancement Benchmarking Quality Control
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Sensor, Signal, and Imaging Informatics.

Yearbook of medical informatics Sep 11, 2017
To summarize significant contributions to sensor, signal, and imaging informatics published in 2016. We conducted an extensive search using PubMed® and Web of Science® to identify the scientific contributions published in 2016 that addressed sensor...
Data Mining Medical Informatics Neoplasms Diagnostic Imaging Pattern Recognition, Automated Systems Integration Humans Machine Learning
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A survey on deep learning in medical image analysis.

Medical image analysis Jul 26, 2017
Deep learning algorithms, in particular convolutional networks, have rapidly become a methodology of choice for analyzing medical images. This paper reviews the major deep learning concepts pertinent to medical image analysis and summarizes over 300 ...
Humans Neural Networks, Computer Image Processing, Computer-Assisted Diagnostic Imaging Machine Learning Algorithms
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Deep learning poised to revolutionise diagnostic imaging.

The Lancet. Respiratory medicine Jul 19, 2017
Image Interpretation, Computer-Assisted Diagnostic Imaging Lung Diseases Humans Machine Learning Pulmonary Disease, Chronic Obstructive Tomography, X-Ray Computed Sensitivity and Specificity
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Overview of deep learning in medical imaging.

Radiological physics and technology Jul 8, 2017
The use of machine learning (ML) has been increasing rapidly in the medical imaging field, including computer-aided diagnosis (CAD), radiomics, and medical image analysis. Recently, an ML area called deep learning emerged in the computer vision field...
Image Processing, Computer-Assisted Diagnostic Imaging Machine Learning
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Deep Learning- and Transfer Learning-Based Super Resolution Reconstruction from Single Medical Image.

Journal of healthcare engineering Jul 6, 2017
Medical images play an important role in medical diagnosis and research. In this paper, a transfer learning- and deep learning-based super resolution reconstruction method is introduced. The proposed method contains one bicubic interpolation template...
Image Processing, Computer-Assisted Algorithms Diagnostic Imaging Deep Learning
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Medical image classification based on multi-scale non-negative sparse coding.

Artificial intelligence in medicine May 27, 2017
With the rapid development of modern medical imaging technology, medical image classification has become more and more important in medical diagnosis and clinical practice. Conventional medical image classification algorithms usually neglect the sema...
Image Interpretation, Computer-Assisted Pattern Recognition, Automated Humans Artificial Intelligence ROC Curve Predictive Value of Tests Diagnostic Imaging
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