AIMC Topic: Magnetic Resonance Imaging

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Cross-Modality Translation with Generative Adversarial Networks to Unveil Alzheimer's Disease Biomarkers.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Generative approaches for cross-modality transformation have recently gained significant attention in neuroimaging. While most previous work has focused on case-control data, the application of generative models to disorder-specific datasets and thei...

ANTs, BET, or…neither? An exploration of brain masking and machine learning tools applied to magnetic resonance elastography.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Magnetic resonance elastography is a quantitative MRI modality that can aid in diagnosis of disease by detecting altered tissue mechanical properties. While brain masking tools exist for common MRI sequences, such as T1-weighted and T2-weighted imagi...

Adaptive High-frequency Enhancement Network with Equilibrated Mechanism for MR Imaging.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Unrolling is a promising deep learning (DL)-based technique in accelerating Magnetic Resonance (MR) imaging. It incorporates deep learning networks into the iterative optimization algorithm, enabling the flexible and adaptive learning of undefined pa...

Feature Imitating Networks Enhance the Performance, Reliability and Speed of Deep Learning on Biomedical Image Processing Tasks.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Feature-Imitating-Networks (FINs) are neural networks that are first trained to approximate closed-form statistical features (e.g. Entropy), and then embedded into other networks to enhance their performance. In this work, we perform the first evalua...

CBAM_SAUNet: A novel attention U-Net for effective segmentation of corner cases.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
U-Net has been demonstrated to be effective for the task of medical image segmentation. Additionally, integrating attention mechanism into U-Net has been shown to yield significant benefits. The Shape Attentive U-Net (SAUNet) is one such recently pro...

Toward Autonomous Marker Localization for Lumbar Epidural Steroid Injection Robot.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
This study compares the effectiveness of the traditional minimum circle detection strategy, i.e. Welzl's algorithm, and the state-of-the-art nnU-Net in the localization of lumbar Epidural Steroid Injection (ESI) robot markers across different imaging...

Unsupervised Anomaly Detection by Learning Elastic Transformations Within an Autoencoder Approach.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Machine learning has approached magnetic resonance image (MRI) analysis using multiple techniques, including deep supervised learning methodologies, where lesions such as tumors or features associated with defined pathologies have been identified sat...

CGDM-GAN: An Adversarial Network Approach with Self-supervised Learning for Site Effect Removal.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Imaging data collected from different sites is difficult to pool together due to unwarranted variations introduced by different acquisition protocols or scanners. Data harmonization is an effective way to mitigate site-specific bias while preserving ...

Stiffness analysis of meningiomas using neural network-based inversion on MR Elastography.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Meningiomas are the most prevalent benign intracranial tumors, and surgical intervention is the primary treatment. The physical characteristics of meningiomas, such as tumor stiffness or consistency, play a crucial role in the surgical approach. This...

Multi-class Prediction of Cognitively Normal / Mild Cognitive Impairment / Alzheimer's Disease Status in Dementia Based on Convolutional Neural Networks with Attention Mechanism.

Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
Alzheimer's disease (AD) is a neurodegenerative disease with insidious onset and progressive development. AD is a health issue that is attracting attention as the world's populations get older. Although there is currently no effective treatment for t...