AIMC Topic: Deep Learning
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Multi-modal MRI synthesis with conditional latent diffusion models for data augmentation in tumor segmentation.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Mar 21, 2025
Multimodality is often necessary for improving object segmentation tasks, especially in the case of multilabel tasks, such as tumor segmentation, which is crucial for clinical diagnosis and treatment planning. However, a major challenge in utilizing ...
A first explainable-AI-based workflow integrating forward-forward and backpropagation-trained networks of label-free multiphoton microscopy images to assess human biopsies of rare neuromuscular disease.
Computer methods and programs in biomedicine
Mar 21, 2025
BACKGROUND AND OBJECTIVE: Diagnosis of rare neuromuscular diseases often relies on muscle biopsy analysis, which varies based on the evaluator's experience. Advances in deep learning show promise in improving diagnostic accuracy by identifying standa...
High-level visual processing in the lateral geniculate nucleus revealed using goal-driven deep learning.
Journal of neuroscience methods
Mar 21, 2025
BACKGROUND: The Lateral Geniculate Nucleus (LGN) is an essential contributor to high-level visual processing despite being an early subcortical area in the visual system. Current LGN computational models focus on its basic properties, with less empha...
Brain tumor segmentation with deep learning: Current approaches and future perspectives.
Journal of neuroscience methods
Mar 21, 2025
BACKGROUND: Accurate brain tumor segmentation from MRI images is critical in the medical industry, directly impacts the efficacy of diagnostic and treatment plans. Accurate segmentation of tumor region can be challenging, especially when noise and ab...
HistoMSC: Density and topology analysis for AI-based visual annotation of histopathology whole slide images.
Computers in biology and medicine
Mar 21, 2025
We introduce an end-to-end framework for the automated visual annotation of histopathology whole slide images. Our method integrates deep learning models to achieve precise localization and classification of cell nuclei with spatial data aggregation ...
Capsule DenseNet++: Enhanced autism detection framework with deep learning and reinforcement learning-based lifestyle recommendation.
Computers in biology and medicine
Mar 21, 2025
Autism Spectrum Disorder (ASD) is a complex neurological condition that impairs the ability to interact, communicate, and behave. It is becoming increasingly prevalent worldwide, with an increase in the number of young children diagnosed with ASD in ...
AI-based deformable hippocampal mesh reflects hippocampal morphological characteristics in relation to cognition in healthy older adults.
NeuroImage
Mar 21, 2025
Magnetic resonance imaging (MRI)-derived hippocampus measurements have been associated with different cognitive domains. The knowledge of hippocampal structural deformations as we age has contributed to our understanding of the overall aging process....
Deep Learning-Based Event Counting for Apnea-Hypopnea Index Estimation Using Recursive Spiking Neural Networks.
IEEE transactions on bio-medical engineering
Mar 21, 2025
OBJECTIVE: To develop a novel method for improved screening of sleep apnea in home environments, focusing on reliable estimation of the Apnea-Hypopnea Index (AHI) without the need for highly precise event localization.
PULSE: A DL-Assisted Physics-Based Approach to the Inverse Problem of Electrocardiography.
IEEE transactions on bio-medical engineering
Mar 21, 2025
This study introduces an innovative approach combining deep-learning techniques with classical physics-based electrocardiographic imaging (ECGI) methods. Our objective is to enhance the accuracy and robustness of ECGI reconstructions. We reshape the ...
Personalized Blood Glucose Forecasting From Limited CGM Data Using Incrementally Retrained LSTM.
IEEE transactions on bio-medical engineering
Mar 21, 2025
For people with Type 1 diabetes (T1D), accurate blood glucose (BG) forecasting is crucial for the effective delivery of insulin by Artificial Pancreas (AP) systems. Deep learning frameworks like Long Short-Term-Memory (LSTM) have been widely used to ...
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