AIMC Topic:
Image Interpretation, Computer-Assisted

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Enlarged perivascular spaces in brain MRI: Automated quantification in four regions.

NeuroImage Oct 13, 2018
Enlarged perivascular spaces (PVS) are structural brain changes visible in MRI, are common in aging, and are considered a reflection of cerebral small vessel disease. As such, assessing the burden of PVS has promise as a brain imaging marker. Visual ...
Humans Brain Female Cerebral Small Vessel Diseases Glymphatic System Aged Male Deep Learning Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Neuroimaging
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Path R-CNN for Prostate Cancer Diagnosis and Gleason Grading of Histological Images.

IEEE transactions on medical imaging Oct 12, 2018
Prostate cancer is the most common and second most deadly form of cancer in men in the United States. The classification of prostate cancers based on Gleason grading using histological images is important in risk assessment and treatment planning for...
Prostatic Neoplasms Neoplasm Grading Prostate Image Interpretation, Computer-Assisted Histocytochemistry Humans Neural Networks, Computer Male
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Deep Geodesic Learning for Segmentation and Anatomical Landmarking.

IEEE transactions on medical imaging Oct 12, 2018
In this paper, we propose a novel deep learning framework for anatomy segmentation and automatic landmarking. Specifically, we focus on the challenging problem of mandible segmentation from cone-beam computed tomography (CBCT) scans and identificatio...
Anatomic Landmarks Algorithms Image Interpretation, Computer-Assisted Female Young Adult Craniofacial Abnormalities Humans Adult Child Cone-Beam Computed Tomography Male Mandible Deep Learning Adolescent
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Using deep autoencoders to identify abnormal brain structural patterns in neuropsychiatric disorders: A large-scale multi-sample study.

Human brain mapping Oct 11, 2018
Machine learning is becoming an increasingly popular approach for investigating spatially distributed and subtle neuroanatomical alterations in brain-based disorders. However, some machine learning models have been criticized for requiring a large nu...
Schizophrenia Image Interpretation, Computer-Assisted Neuroimaging Male Deep Learning Magnetic Resonance Imaging Humans Female Autism Spectrum Disorder Adult Brain
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Deep Learning to Distinguish Recalled but Benign Mammography Images in Breast Cancer Screening.

Clinical cancer research : an official journal of the American Association for Cancer Research Oct 11, 2018
PURPOSE: False positives in digital mammography screening lead to high recall rates, resulting in unnecessary medical procedures to patients and health care costs. This study aimed to investigate the revolutionary deep learning methods to distinguish...
Early Detection of Cancer Public Health Surveillance Mammography ROC Curve Image Processing, Computer-Assisted Mass Screening Image Interpretation, Computer-Assisted Humans Retrospective Studies Female Reproducibility of Results Breast Neoplasms Deep Learning
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Development and validation of a deep-learning algorithm for the detection of polyps during colonoscopy.

Nature biomedical engineering Oct 10, 2018
The detection and removal of precancerous polyps via colonoscopy is the gold standard for the prevention of colon cancer. However, the detection rate of adenomatous polyps can vary significantly among endoscopists. Here, we show that a machine-learni...
ROC Curve Databases, Factual Humans Colonic Polyps Area Under Curve Image Interpretation, Computer-Assisted Colonoscopy Software Colonic Neoplasms Precancerous Conditions Deep Learning Algorithms
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Infant Brain Development Prediction With Latent Partial Multi-View Representation Learning.

IEEE transactions on medical imaging Oct 9, 2018
The early postnatal period witnesses rapid and dynamic brain development. However, the relationship between brain anatomical structure and cognitive ability is still unknown. Currently, there is no explicit model to characterize this relationship in ...
Algorithms Infant, Newborn Infant Child, Preschool Humans Machine Learning Cerebral Cortex Longitudinal Studies Magnetic Resonance Imaging Image Interpretation, Computer-Assisted
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Deep Learning for Cardiac MRI: The Time Has Come.

Radiology Oct 9, 2018
Magnetic Resonance Imaging Ventricular Function, Left Heart Ventricles Deep Learning Image Interpretation, Computer-Assisted
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Deep Learning-based Method for Fully Automatic Quantification of Left Ventricle Function from Cine MR Images: A Multivendor, Multicenter Study.

Radiology Oct 9, 2018
Purpose To develop a deep learning-based method for fully automated quantification of left ventricular (LV) function from short-axis cine MR images and to evaluate its performance in a multivendor and multicenter setting. Materials and Methods This r...
Ventricular Function Heart Ventricles Image Interpretation, Computer-Assisted Magnetic Resonance Imaging, Cine Humans Retrospective Studies Deep Learning
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Artificial Intelligence-Based Breast Cancer Nodal Metastasis Detection: Insights Into the Black Box for Pathologists.

Archives of pathology & laboratory medicine Oct 8, 2018
CONTEXT.—: Nodal metastasis of a primary tumor influences therapy decisions for a variety of cancers. Histologic identification of tumor cells in lymph nodes can be laborious and error-prone, especially for small tumor foci.
Humans Female Pathologists Image Interpretation, Computer-Assisted Sentinel Lymph Node Biopsy Pathology, Clinical Breast Neoplasms Deep Learning Lymphatic Metastasis
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