AIMC Topic: Image Processing, Computer-Assisted

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Review of GPU-based Monte Carlo simulation platforms for transmission and emission tomography in medicine.

Physics in medicine and biology
. Monte Carlo (MC) simulation remains the gold standard for modeling complex physical interactions in transmission and emission tomography, with graphic processing unit (GPU) parallel computing offering unmatched computational performance and enablin...

SamRobNODDI:-space sampling-augmented continuous representation learning for robust and generalized NODDI.

Physics in medicine and biology
. Neurite orientation dispersion and density imaging (NODDI) microstructure estimation from diffusion magnetic resonance imaging (dMRI) is of great significance for the discovery and treatment of various neurological diseases. Current deep learning-b...

A simple and effective approach for body part recognition on CT scans based on projection estimation.

Scientific reports
It is well known that machine learning models require a high amount of annotated data to obtain optimal performance. Labelling Computed Tomography (CT) data can be a particularly challenging task due to its volumetric nature and often missing and/or ...

Deep learning-based automatic facial symmetry scoring in peripheral facial palsy.

Scientific reports
Unilateral peripheral facial palsy (PFP) results in facial asymmetry and functional impairment, reducing quality of life. Accurate, objective assessment is vital for monitoring and rehabilitation. This study presents an automated method utilizes stan...

A comparative analysis of deep learning architectures for thyroid tissue classification with hyperspectral imaging.

Scientific reports
Hyperspectral imaging has shown significant applicability in the medical field, particularly for its ability to represent spectral information that can differentiate specific biomolecular characteristics in tissue samples. However, the complexity of ...

Optimized deep learning for brain tumor detection: a hybrid approach with attention mechanisms and clinical explainability.

Scientific reports
Brain tumor classification (BTC) from Magnetic Resonance Imaging (MRI) is a critical diagnosis task, which is highly important for treatment planning. In this study, we propose a hybrid deep learning (DL) model that integrates VGG16, an attention mec...

Integrating snapshot ensemble learning into masked autoencoders for efficient self-supervised pretraining in medical imaging.

Scientific reports
Self-supervised learning (SSL) has gained significant attention in medical imaging for its ability to leverage large amounts of unlabeled data for effective model pretraining. Among SSL methods, the masked autoencoder (MAE) has proven robust in learn...

The analysis of landscape design and plant selection under deep learning.

Scientific reports
This paper explores the application of deep learning (DL) techniques in landscape design and plant selection, aiming to enhance design efficiency and quality through automated plant leaf image recognition (PLIR). A novel framework based on Convolutio...

A novel residual network based on multidimensional attention and pinwheel convolution for brain tumor classification.

Scientific reports
Early and accurate brain tumor classification is vital for clinical diagnosis and treatment. Although Convolutional Neural Networks (CNNs) are widely used in medical image analysis, they often struggle to focus on critical information adequately and ...

Multi-kernel inception-enhanced vision transformer for plant leaf disease recognition.

Scientific reports
The timely and precise identification of diseases in plants is essential for efficient disease control and safeguarding of crops. Manual identification of diseases requires expert knowledge in the field, and finding people with domain knowledge is ch...