AIMC Topic: Image Interpretation, Computer-Assisted
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Are we at a crossroads or a plateau? Radiomics and machine learning in abdominal oncology imaging.
Abdominal radiology (New York)
Jun 1, 2019
Advances in radiomics and machine learning have driven a technology boom in the automated analysis of radiology images. For the past several years, expectations have been nearly boundless for these new technologies to revolutionize radiology image an...
Transfer learning on T1-weighted images for brain age estimation.
Mathematical biosciences and engineering : MBE
May 18, 2019
Due to both the hidden nature and the irreversibility of Alzheimers disease (AD), it has become the killer of the elderly and is thus the focus of much attention in the medical field. Radiologists compare the predicted brain age with the ground truth...
Digital pathology and artificial intelligence.
The Lancet. Oncology
May 1, 2019
In modern clinical practice, digital pathology has a crucial role and is increasingly a technological requirement in the scientific laboratory environment. The advent of whole-slide imaging, availability of faster networks, and cheaper storage soluti...
Machine learning based automated dynamic quantification of left heart chamber volumes.
European heart journal. Cardiovascular Imaging
May 1, 2019
AIMS: Studies have demonstrated the ability of a new automated algorithm for volumetric analysis of 3D echocardiographic (3DE) datasets to provide accurate and reproducible measurements of left ventricular and left atrial (LV, LA) volumes at end-syst...
Predicting Breast Cancer Molecular Subtype with MRI Dataset Utilizing Convolutional Neural Network Algorithm.
Journal of digital imaging
Apr 1, 2019
To develop a convolutional neural network (CNN) algorithm that can predict the molecular subtype of a breast cancer based on MRI features. An IRB-approved study was performed in 216 patients with available pre-treatment MRIs and immunohistochemical s...
The Residual Center of Mass: An Image Descriptor for the Diagnosis of Alzheimer Disease.
Neuroinformatics
Apr 1, 2019
A crucial quest in neuroimaging is the discovery of image features (biomarkers) associated with neurodegenerative disorders. Recent works show that such biomarkers can be obtained by image analysis techniques. However, these techniques cannot be dire...
Optical biopsy of head and neck cancer using hyperspectral imaging and convolutional neural networks.
Journal of biomedical optics
Mar 1, 2019
For patients undergoing surgical cancer resection of squamous cell carcinoma (SCCa), cancer-free surgical margins are essential for good prognosis. We developed a method to use hyperspectral imaging (HSI), a noncontact optical imaging modality, and c...
Deep Learning Predicts OCT Measures of Diabetic Macular Thickening From Color Fundus Photographs.
Investigative ophthalmology & visual science
Mar 1, 2019
PURPOSE: To develop deep learning (DL) models for the automatic detection of optical coherence tomography (OCT) measures of diabetic macular thickening (MT) from color fundus photographs (CFPs).
Diabetic Retinopathy
Tomography, Optical Coherence
Neural Networks, Computer
Fundus Oculi
Retrospective Studies
Humans
Macular Edema
Macula Lutea
Female
Image Interpretation, Computer-Assisted
Vascular Endothelial Growth Factor A
Ranibizumab
Sensitivity and Specificity
Angiogenesis Inhibitors
Photography
Male
False Positive Reactions
Middle Aged
Randomized Controlled Trials as Topic
Intravitreal Injections
Deep Learning
Predictive Value of Tests
Diagnostic Techniques, Ophthalmological
Screening Glaucoma With Red-free Fundus Photography Using Deep Learning Classifier and Polar Transformation.
Journal of glaucoma
Mar 1, 2019
UNLABELLED: PRéCIS:: The novel proposed algorithm using deep learning classifier and polar transformation technique can be an economical as well as an effective tool for early detection of glaucomatous RNFL defect.
ROC Curve
Area Under Curve
Tomography, Optical Coherence
Image Interpretation, Computer-Assisted
Nerve Fibers
Retinal Ganglion Cells
Ophthalmologic Surgical Procedures
Diagnostic Techniques, Ophthalmological
Humans
Intraocular Pressure
Retrospective Studies
Male
Photography
Female
Middle Aged
Glaucoma, Open-Angle
Adult
Deep Learning
Artificial Intelligence-Assisted Gastroenterology- Promises and Pitfalls.
The American journal of gastroenterology
Mar 1, 2019
Technological advances in artificial intelligence (AI) represent an enticing opportunity to benefit gastroenterological practice. Moreover, AI, through machine or deep learning, permits the ability to develop predictive models from large datasets. Po...
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