AIMC Topic:
Image Interpretation, Computer-Assisted
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Microaneurysm Detection Using Principal Component Analysis and Machine Learning Methods.
IEEE transactions on nanobioscience
May 24, 2018
Diabetic retinopathy (DR) is an eye abnormality caused by long-term diabetes and it is the most common cause of blindness before the age of 50. Microaneurysms (MAs), resulting from leakage from retinal blood vessels, are early indicators of DR. In th...
A Novel Method to Predict Knee Osteoarthritis Progression on MRI Using Machine Learning Methods.
IEEE transactions on nanobioscience
May 24, 2018
This paper explored the hidden biomedical information from knee magnetic resonance (MR) images for osteoarthritis (OA) prediction. We have computed the cartilage damage index (CDI) information from 36 informative locations on tibiofemoral cartilage c...
Integrating spatial-anatomical regularization and structure sparsity into SVM: Improving interpretation of Alzheimer's disease classification.
NeuroImage
May 23, 2018
In recent years, machine learning approaches have been successfully applied to the field of neuroimaging for classification and regression tasks. However, many approaches do not give an intuitive relation between the raw features and the diagnosis. T...
Computer-assisted liver graft steatosis assessment via learning-based texture analysis.
International journal of computer assisted radiology and surgery
May 23, 2018
PURPOSE: Fast and accurate graft hepatic steatosis (HS) assessment is of primary importance for lowering liver dysfunction risks after transplantation. Histopathological analysis of biopsied liver is the gold standard for assessing HS, despite being ...
Structure-Preserving Guided Retinal Image Filtering and Its Application for Optic Disk Analysis.
IEEE transactions on medical imaging
May 21, 2018
Retinal fundus photographs have been used in the diagnosis of many ocular diseases such as glaucoma, pathological myopia, age-related macular degeneration, and diabetic retinopathy. With the development of computer science, computer aided diagnosis h...
Automated comprehensive Adolescent Idiopathic Scoliosis assessment using MVC-Net.
Medical image analysis
May 18, 2018
Automated quantitative estimation of spinal curvature is an important task for the ongoing evaluation and treatment planning of Adolescent Idiopathic Scoliosis (AIS). It solves the widely accepted disadvantage of manual Cobb angle measurement (time-c...
Deep Learning Techniques for Automatic MRI Cardiac Multi-Structures Segmentation and Diagnosis: Is the Problem Solved?
IEEE transactions on medical imaging
May 17, 2018
Delineation of the left ventricular cavity, myocardium, and right ventricle from cardiac magnetic resonance images (multi-slice 2-D cine MRI) is a common clinical task to establish diagnosis. The automation of the corresponding tasks has thus been th...
Machine Learning-based Texture Analysis of Contrast-enhanced MR Imaging to Differentiate between Glioblastoma and Primary Central Nervous System Lymphoma.
Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine
May 16, 2018
PURPOSE: Although advanced MRI techniques are increasingly available, imaging differentiation between glioblastoma and primary central nervous system lymphoma (PCNSL) is sometimes confusing. We aimed to evaluate the performance of image classificatio...
Segmentation of histological images and fibrosis identification with a convolutional neural network.
Computers in biology and medicine
May 16, 2018
Segmentation of histological images is one of the most crucial tasks for many biomedical analyses involving quantification of certain tissue types, such as fibrosis via Masson's trichrome staining. However, challenges are posed by the high variabilit...
Detecting and Locating Gastrointestinal Anomalies Using Deep Learning and Iterative Cluster Unification.
IEEE transactions on medical imaging
May 15, 2018
This paper proposes a novel methodology for automatic detection and localization of gastrointestinal (GI) anomalies in endoscopic video frame sequences. Training is performed with weakly annotated images, using only image-level, semantic labels inste...
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