AIMC Topic: Magnetic Resonance Imaging
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Hahn-PCNN-CNN: an end-to-end multi-modal brain medical image fusion framework useful for clinical diagnosis.
BMC medical imaging
Jul 14, 2021
BACKGROUND: In medical diagnosis of brain, the role of multi-modal medical image fusion is becoming more prominent. Among them, there is no lack of filtering layered fusion and newly emerging deep learning algorithms. The former has a fast fusion spe...
Deep Learning on MRI Images for Diagnosis of Lung Cancer Spinal Bone Metastasis.
Contrast media & molecular imaging
Jul 14, 2021
This paper aimed to explore the adoption of deep learning algorithms in lung cancer spinal bone metastasis diagnosis. Comprehensive analysis was carried out with the aid of AdaBoost algorithm and Chan-Vese (CV) algorithm. 87 patients with lung cancer...
Use of Deep-Learning Genomics to Discriminate Healthy Individuals from Those with Alzheimer's Disease or Mild Cognitive Impairment.
Behavioural neurology
Jul 14, 2021
OBJECTIVES: Alzheimer's disease (AD) is the most prevalent neurodegenerative disorder and the most common form of dementia in the elderly. Certain genes have been identified as important clinical risk factors for AD, and technological advances in gen...
Robotic guidance platform for laser interstitial thermal ablation and stereotactic needle biopsies: a single center experience.
Journal of robotic surgery
Jul 13, 2021
While laser ablation has become an increasingly important tool in the neurosurgical oncologist's armamentarium, deep seated lesions, and those located near critical structures require utmost accuracy during stereotactic laser catheter placement. Robo...
Accelerate gas diffusion-weighted MRI for lung morphometry with deep learning.
European radiology
Jul 13, 2021
OBJECTIVES: Multiple b-value gas diffusion-weighted MRI (DW-MRI) enables non-invasive and quantitative assessment of lung morphometry, but its long acquisition time is not well-tolerated by patients. We aimed to accelerate multiple b-value gas DW-MRI...
Y-net: a reducing gaussian noise convolutional neural network for MRI brain tumor classification with NADE concatenation.
Biomedical physics & engineering express
Jul 13, 2021
Brain tumors are among the most serious cancers that can have a negative impact on a person's quality of life. The magnetic resonance imaging (MRI) analysis detects abnormal cell growth in the skull. Recently, machine learning models such as artifici...
Three-dimensional deep learning with spatial erasing for unsupervised anomaly segmentation in brain MRI.
International journal of computer assisted radiology and surgery
Jul 12, 2021
PURPOSE: Brain Magnetic Resonance Images (MRIs) are essential for the diagnosis of neurological diseases. Recently, deep learning methods for unsupervised anomaly detection (UAD) have been proposed for the analysis of brain MRI. These methods rely on...
[MRI-guided minimally invasive treatment of prostate cancer].
Der Radiologe
Jul 12, 2021
CLINICAL/METHODOLOGICAL ISSUE: Multiparametric magnetic resonance imaging (mpMRI) of the prostate plays a crucial role in the diagnosis and local staging of primary prostate cancer.
Deep learning in magnetic resonance image reconstruction.
Journal of medical imaging and radiation oncology
Jul 12, 2021
Magnetic resonance (MR) imaging visualises soft tissue contrast in exquisite detail without harmful ionising radiation. In this work, we provide a state-of-the-art review on the use of deep learning in MR image reconstruction from different image acq...
A Comprehensive Study of Data Augmentation Strategies for Prostate Cancer Detection in Diffusion-Weighted MRI Using Convolutional Neural Networks.
Journal of digital imaging
Jul 12, 2021
Data augmentation refers to a group of techniques whose goal is to battle limited amount of available data to improve model generalization and push sample distribution toward the true distribution. While different augmentation strategies and their co...
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