AIMC Topic:
Image Interpretation, Computer-Assisted

Clear Filters Showing 1571 to 1580 of 2721 articles

Regularized siamese neural network for unsupervised outlier detection on brain multiparametric magnetic resonance imaging: Application to epilepsy lesion screening.

Medical image analysis Nov 21, 2019
In this study, we propose a novel anomaly detection model targeting subtle brain lesions in multiparametric MRI. To compensate for the lack of annotated data adequately sampling the heterogeneity of such pathologies, we cast this problem as an outlie...
Neural Networks, Computer Female Aged Adult Humans Male Middle Aged Adolescent Image Interpretation, Computer-Assisted Magnetic Resonance Imaging Datasets as Topic Unsupervised Machine Learning Epilepsy
View on PubMed DOI

Celiac disease diagnosis from videocapsule endoscopy images with residual learning and deep feature extraction.

Computer methods and programs in biomedicine Nov 20, 2019
BACKGROUND AND OBJECTIVE: Videocapsule endoscopy (VCE) is a relatively new technique for evaluating the presence of villous atrophy in celiac disease patients. The diagnostic analysis of video frames is currently time-consuming and tedious. Recently,...
Celiac Disease Image Interpretation, Computer-Assisted Linear Models Calibration Capsule Endoscopy Sensitivity and Specificity Diagnosis, Computer-Assisted Machine Learning Deep Learning Image Processing, Computer-Assisted Algorithms Discriminant Analysis Reproducibility of Results Light Support Vector Machine Humans Endoscopy Intestinal Mucosa Video Recording
View on PubMed DOI

Uncertainty and interpretability in convolutional neural networks for semantic segmentation of colorectal polyps.

Medical image analysis Nov 20, 2019
Colorectal polyps are known to be potential precursors to colorectal cancer, which is one of the leading causes of cancer-related deaths on a global scale. Early detection and prevention of colorectal cancer is primarily enabled through manual screen...
Uncertainty Colonic Polyps Image Interpretation, Computer-Assisted Semantics Monte Carlo Method Neural Networks, Computer Humans Decision Support Techniques Colonoscopy Deep Learning
View on PubMed DOI

Comparison of morphometric parameters in prediction of hydrocephalus using random forests.

Computers in biology and medicine Nov 20, 2019
Ventricles of the human brain enlarge with aging, neurodegenerative diseases, intrinsic, and extrinsic pathologies. The morphometric examination of neuroimages is an effective approach to assess structural changes occurring due to diseases such as hy...
Adult Hydrocephalus Female Child, Preschool Humans Male Image Interpretation, Computer-Assisted Child Aged Machine Learning Middle Aged Cerebral Ventricles Magnetic Resonance Imaging Aged, 80 and over Algorithms Adolescent Decision Trees Young Adult Brain
View on PubMed DOI

A fuzzy clustering based color-coded diagram for effective illustration of blood perfusion parameters in contrast-enhanced ultrasound videos.

Computer methods and programs in biomedicine Nov 19, 2019
BACKGROUND AND OBJECTIVE: Early identification and diagnosis of tumors are of great significance to improve the survival rate of patients. Amongst other techniques, contrast-enhanced ultrasound is an important means to help doctors diagnose tumors. D...
Humans Algorithms Neoplasms Ultrasonography Contrast Media Fuzzy Logic Cluster Analysis Color Perfusion Image Interpretation, Computer-Assisted
View on PubMed DOI

Lymph Node Metastasis Prediction from Primary Breast Cancer US Images Using Deep Learning.

Radiology Nov 19, 2019
Background Deep learning (DL) algorithms are gaining extensive attention for their excellent performance in image recognition tasks. DL models can automatically make a quantitative assessment of complex medical image characteristics and achieve incre...
Adult Sensitivity and Specificity Breast Neoplasms Middle Aged Female Aged Aged, 80 and over Young Adult Predictive Value of Tests Ultrasonography, Mammary Feasibility Studies Image Interpretation, Computer-Assisted Deep Learning Cohort Studies Lymph Nodes Lymphatic Metastasis Humans Neural Networks, Computer Algorithms Retrospective Studies
View on PubMed DOI

Machine learning-based quantitative texture analysis of conventional MRI combined with ADC maps for assessment of IDH1 mutation in high-grade gliomas.

Japanese journal of radiology Nov 18, 2019
PURPOSE: To assess the performance of texture analysis of conventional magnetic resonance imaging (MRI) and apparent diffusion coefficient (ADC) maps in predicting IDH1 status in high-grade gliomas (HGG).
Humans Middle Aged Glioma Magnetic Resonance Imaging Predictive Value of Tests Reproducibility of Results Machine Learning Mutation Adult Isocitrate Dehydrogenase Brain Image Interpretation, Computer-Assisted Brain Neoplasms Retrospective Studies Male Female
View on PubMed DOI

Fully Automated Segmentation Algorithm for Hematoma Volumetric Analysis in Spontaneous Intracerebral Hemorrhage.

Stroke Nov 18, 2019
Background and Purpose- Hematoma volume measurements influence prognosis and treatment decisions in patients with spontaneous intracerebral hemorrhage (ICH). The aims of this study are to derive and validate a fully automated segmentation algorithm f...
Cerebral Hemorrhage Hematoma Image Interpretation, Computer-Assisted Neuroimaging Humans Deep Learning
View on PubMed DOI

Deep-UV excitation fluorescence microscopy for detection of lymph node metastasis using deep neural network.

Scientific reports Nov 15, 2019
Deep-UV (DUV) excitation fluorescence microscopy has potential to provide rapid diagnosis with simple technique comparing to conventional histopathology based on hematoxylin and eosin (H&E) staining. We established a fluorescent staining protocol for...
Humans Neural Networks, Computer Machine Learning Software Microscopy, Fluorescence Biopsy Image Interpretation, Computer-Assisted Immunohistochemistry Fluorescent Antibody Technique Algorithms Image Processing, Computer-Assisted Lymph Nodes Lymphatic Metastasis
View on PubMed DOI

Statistical modeling and knowledge-based segmentation of cerebral artery based on TOF-MRA and MR-T1.

Computer methods and programs in biomedicine Nov 14, 2019
BACKGROUND AND OBJECTIVE: For cerebrovascular segmentation from time-of-flight (TOF) magnetic resonance angiography (MRA), the focused issues are segmentation accuracy, vascular network coverage ratio, and cerebral artery and vein (CA/CV) separation....
Knowledge Bases Image Interpretation, Computer-Assisted Magnetic Resonance Angiography Cerebral Arteries Humans Algorithms Models, Statistical
View on PubMed DOI
Popular Topics
Recent Journals