AIMC Topic: Image Processing, Computer-Assisted

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Exploring the potential performance of 0.2 T low-field unshielded MRI scanner using deep learning techniques.

Magma (New York, N.Y.) Feb 18, 2025
OBJECTIVE: Using deep learning-based techniques to overcome physical limitations and explore the potential performance of 0.2 T low-field unshielded MRI in terms of imaging quality and speed.
Signal-To-Noise Ratio Phantoms, Imaging Humans Algorithms Deep Learning Image Processing, Computer-Assisted Magnetic Resonance Imaging Equipment Design
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A deep learning detection method for pancreatic cystic neoplasm based on Mamba architecture.

Journal of X-ray science and technology Feb 18, 2025
OBJECTIVE: Early diagnosis of pancreatic cystic neoplasm (PCN) is crucial for patient survival. This study proposes M-YOLO, a novel model combining Mamba architecture and YOLO, to enhance the detection of pancreatic cystic tumors. The model addresses...
Humans Pancreatic Cyst Image Processing, Computer-Assisted Algorithms Pancreatic Neoplasms Tomography, X-Ray Computed Image Interpretation, Computer-Assisted Sensitivity and Specificity Deep Learning
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The development of an artificial intelligence auto-segmentation tool for 3D volumetric analysis of vestibular schwannomas.

Scientific reports Feb 18, 2025
Linear and volumetric analysis are the typical methods to measure tumor size. 3D volumetric analysis has risen in popularity; however, this is very time and labor intensive limiting its implementation in clinical practice. This study aims to show tha...
Female Adult Male Middle Aged Imaging, Three-Dimensional Magnetic Resonance Imaging Image Processing, Computer-Assisted Tumor Burden Artificial Intelligence Neuroma, Acoustic Software Algorithms Humans
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HDL-ACO hybrid deep learning and ant colony optimization for ocular optical coherence tomography image classification.

Scientific reports Feb 18, 2025
Optical Coherence Tomography (OCT) plays a crucial role in diagnosing ocular diseases, yet conventional CNN-based models face limitations such as high computational overhead, noise sensitivity, and data imbalance. This paper introduces HDL-ACO, a nov...
Deep Learning Humans Image Processing, Computer-Assisted Eye Diseases Neural Networks, Computer Tomography, Optical Coherence Algorithms
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Towards full integration of explainable artificial intelligence in colon capsule endoscopy's pathway.

Scientific reports Feb 18, 2025
Despite recent surge of interest in deploying colon capsule endoscopy (CCE) for early diagnosis of colorectal diseases, there remains a large gap between the current state of CCE in clinical practice, and the state of its counterpart optical colonosc...
Image Processing, Computer-Assisted Colonic Polyps Capsule Endoscopy Colorectal Neoplasms Colon Colonoscopy Artificial Intelligence Algorithms Humans Neural Networks, Computer
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Accelerating veterinary low field MRI acquisitions using the deep learning based denoising solution HawkAI.

Scientific reports Feb 18, 2025
Magnetic resonance imaging (MRI) has changed veterinary diagnosis but its long-sequence time can be problematic, especially because animals need to be sedated during the exam. Unfortunately, shorter scan times implies a fall in overall image quality ...
Signal-To-Noise Ratio Image Processing, Computer-Assisted Magnetic Resonance Imaging Artifacts Algorithms Animals Deep Learning
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Sub-1-min relaxation-enhanced non-contrast non-triggered cervical MRA using compressed SENSE with deep learning reconstruction in healthy volunteers.

European radiology experimental Feb 18, 2025
BACKGROUND: We evaluated the acceleration of a three-dimensional isotropic flow-independent magnetic resonance angiography (MRA) (relaxation-enhanced angiography without contrast and triggering, REACT) of neck arteries using compressed SENSE (CS) com...
Humans Female Middle Aged Deep Learning Imaging, Three-Dimensional Young Adult Adult Male Healthy Volunteers Signal-To-Noise Ratio Magnetic Resonance Angiography Image Processing, Computer-Assisted Neck
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Multi-task learning for automated contouring and dose prediction in radiotherapy.

Physics in medicine and biology Feb 18, 2025
. Deep learning (DL)-based automated contouring and treatment planning has been proven to improve the efficiency and accuracy of radiotherapy. However, conventional radiotherapy treatment planning process has the automated contouring and treatment pl...
Male Deep Learning Image Processing, Computer-Assisted Humans Automation Radiation Dosage Radiotherapy Dosage Head and Neck Neoplasms Prostatic Neoplasms Radiotherapy Planning, Computer-Assisted
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An integrated approach for advanced vehicle classification.

PloS one Feb 18, 2025
This study is dedicated to addressing the trade-off between receptive field size and computational efficiency in low-level vision. Conventional neural networks (CNNs) usually expand the receptive field by adding layers or inflation filtering, which o...
Wavelet Analysis Algorithms Humans Image Processing, Computer-Assisted Neural Networks, Computer Automobiles
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Unsupervised neural network-based image stitching method for bladder endoscopy.

PloS one Feb 18, 2025
Bladder endoscopy enables the observation of intravesical lesion characteristics, making it an essential tool in urology. Image stitching techniques are commonly employed to expand the field of view of bladder endoscopy. Traditional image stitching m...
Urinary Bladder Humans Algorithms Unsupervised Machine Learning Neural Networks, Computer Endoscopy Cystoscopy Image Processing, Computer-Assisted
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