AIMC Topic: Magnetic Resonance Imaging
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A deep learning algorithm for white matter hyperintensity lesion detection and segmentation.
Neuroradiology
Oct 2, 2021
PURPOSE: White matter hyperintensity (WMHI) lesions on MR images are an important indication of various types of brain diseases that involve inflammation and blood vessel abnormalities. Automated quantification of the WMHI can be valuable for the cli...
Predicting the retinotopic organization of human visual cortex from anatomy using geometric deep learning.
NeuroImage
Oct 1, 2021
Whether it be in a single neuron or a more complex biological system like the human brain, form and function are often directly related. The functional organization of human visual cortex, for instance, is tightly coupled with the underlying anatomy ...
CEREBRUM-7T: Fast and Fully Volumetric Brain Segmentation of 7 Tesla MR Volumes.
Human brain mapping
Oct 1, 2021
Ultra-high-field magnetic resonance imaging (MRI) enables sub-millimetre resolution imaging of the human brain, allowing the study of functional circuits of cortical layers at the meso-scale. An essential step in many functional and structural neuroi...
A Unified Framework for Generalized Low-Shot Medical Image Segmentation With Scarce Data.
IEEE transactions on medical imaging
Sep 30, 2021
Medical image segmentation has achieved remarkable advancements using deep neural networks (DNNs). However, DNNs often need big amounts of data and annotations for training, both of which can be difficult and costly to obtain. In this work, we propos...
Editorial Comment: Accelerated Joint MRI With Deep Learning-Based Reconstruction-A Promising Approach to Increasing Imaging Speed Without Compromising Image Quality.
AJR. American journal of roentgenology
Sep 29, 2021
A deep learning based approach identifies regions more relevant than resting-state networks to the prediction of general intelligence from resting-state fMRI.
Human brain mapping
Sep 29, 2021
Prediction of cognitive ability latent factors such as general intelligence from neuroimaging has elucidated questions pertaining to their neural origins. However, predicting general intelligence from functional connectivity limit hypotheses to that ...
Diagnostic test accuracy of artificial intelligence analysis of cross-sectional imaging in pulmonary hypertension: a systematic literature review.
The British journal of radiology
Sep 29, 2021
OBJECTIVES: To undertake the first systematic review examining the performance of artificial intelligence (AI) applied to cross-sectional imaging for the diagnosis of acquired pulmonary arterial hypertension (PAH).
Comparison of different deep learning architectures for synthetic CT generation from MR images.
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Sep 29, 2021
PURPOSE: Among the different available methods for synthetic CT generation from MR images for the task of MR-guided radiation planning, the deep learning algorithms have and do outperform their conventional counterparts. In this study, we investigate...
A Cascaded Deep Learning-Based Artificial Intelligence Algorithm for Automated Lesion Detection and Classification on Biparametric Prostate Magnetic Resonance Imaging.
Academic radiology
Sep 28, 2021
RATIONALE AND OBJECTIVES: Prostate MRI improves detection of clinically significant prostate cancer; however, its diagnostic performance has wide variation. Artificial intelligence (AI) has the potential to assist radiologists in the detection and cl...
An automated liver segmentation in liver iron concentration map using fuzzy c-means clustering combined with anatomical landmark data.
BMC medical imaging
Sep 28, 2021
BACKGROUND: To estimate median liver iron concentration (LIC) calculated from magnetic resonance imaging, excluded vessels of the liver parenchyma region were defined manually. Previous works proposed the automated method for excluding vessels from t...
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