AIMC Topic: Convolutional Neural Networks

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Convolutional Neural Networks for Segmentation of Pleural Mesothelioma: Analysis of Probability Map Thresholds (CALGB 30901, Alliance).

Journal of imaging informatics in medicine Sep 12, 2024
The purpose of this study was to evaluate the impact of probability map threshold on pleural mesothelioma (PM) tumor delineations generated using a convolutional neural network (CNN). One hundred eighty-six CT scans from 48 PM patients were segmented...
Neural Networks, Computer Tomography, X-Ray Computed Female Aged Humans Radiographic Image Interpretation, Computer-Assisted Probability Male Mesothelioma Tumor Burden Middle Aged Pleural Neoplasms Convolutional Neural Networks
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Skeleton-guided 3D convolutional neural network for tubular structure segmentation.

International journal of computer assisted radiology and surgery Sep 12, 2024
PURPOSE: Accurate segmentation of tubular structures is crucial for clinical diagnosis and treatment but is challenging due to their complex branching structures and volume imbalance. The purpose of this study is to propose a 3D deep learning network...
Imaging, Three-Dimensional Radiographic Image Interpretation, Computer-Assisted Humans Neural Networks, Computer Tomography, X-Ray Computed Deep Learning Convolutional Neural Networks
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A 3D Convolutional Neural Network Based on Non-enhanced Brain CT to Identify Patients with Brain Metastases.

Journal of imaging informatics in medicine Aug 26, 2024
Dedicated brain imaging for cancer patients is seldom recommended in the absence of symptoms. There is increasing availability of non-enhanced CT (NE-CT) of the brain, mainly owing to a wider utilization of Positron Emission Tomography-CT (PET-CT) in...
Aged Neural Networks, Computer Aged, 80 and over Brain Adult Humans Retrospective Studies Brain Neoplasms Tomography, X-Ray Computed Male Magnetic Resonance Imaging Female Middle Aged Convolutional Neural Networks Imaging, Three-Dimensional
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Deep Convolutional Neural Network for Automated Staging of Periodontal Bone Loss Severity on Bite-wing Radiographs: An Eigen-CAM Explainability Mapping Approach.

Journal of imaging informatics in medicine Aug 15, 2024
Periodontal disease is a significant global oral health problem. Radiographic staging is critical in determining periodontitis severity and treatment requirements. This study aims to automatically stage periodontal bone loss using a deep learning app...
Male Middle Aged Severity of Illness Index Deep Learning Neural Networks, Computer Female Adult Convolutional Neural Networks Alveolar Bone Loss Humans
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Functional Near-Infrared Spectroscopy-Based Computer-Aided Diagnosis of Major Depressive Disorder Using Convolutional Neural Network with a New Channel Embedding Layer Considering Inter-Hemispheric Asymmetry in Prefrontal Hemodynamic Responses.

Depression and anxiety Jul 14, 2024
BACKGROUND: Functional near-infrared spectroscopy (fNIRS) is being extensively explored as a potential primary screening tool for major depressive disorder (MDD) because of its portability, cost-effectiveness, and low susceptibility to motion artifac...
Functional Neuroimaging Middle Aged Young Adult Diagnosis, Computer-Assisted Depressive Disorder, Major Adult Deep Learning Convolutional Neural Networks Spectroscopy, Near-Infrared Male Prefrontal Cortex Humans Hemodynamics Neural Networks, Computer Female
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Improved deep learning for automatic localisation and segmentation of rectal cancer on T2-weighted MRI.

Journal of medical radiation sciences Apr 24, 2024
INTRODUCTION: The automatic segmentation approaches of rectal cancer from magnetic resonance imaging (MRI) are very valuable to relieve physicians from heavy workloads and enhance working efficiency. This study aimed to compare the segmentation accur...
Image Processing, Computer-Assisted Humans Male Adenocarcinoma Retrospective Studies Magnetic Resonance Imaging Middle Aged Deep Learning Rectal Neoplasms Female Convolutional Neural Networks
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Automated Detection of Cerebral Microbleeds on Two-dimensional Gradient-recalled Echo T2* Weighted Images Using a Morphology Filter Bank and Convolutional Neural Network.

Magnetic resonance in medical sciences : MRMS : an official journal of Japan Society of Magnetic Resonance in Medicine Mar 15, 2024
PURPOSE: We present a novel algorithm for the automated detection of cerebral microbleeds (CMBs) on 2D gradient-recalled echo T2* weighted images (T2*WIs). This approach combines a morphology filter bank with a convolutional neural network (CNN) to i...
Male Middle Aged Convolutional Neural Networks Cerebral Hemorrhage Image Interpretation, Computer-Assisted Image Processing, Computer-Assisted Magnetic Resonance Imaging Female Aged Aged, 80 and over Algorithms Brain Retrospective Studies Humans Neural Networks, Computer
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A multi-branch convolutional neural network for snoring detection based on audio.

Computer methods in biomechanics and biomedical engineering Feb 19, 2024
Obstructive sleep apnea (OSA) is associated with various health complications, and snoring is a prominent characteristic of this disorder. Therefore, the exploration of a concise and effective method for detecting snoring has consistently been a cruc...
Neural Networks, Computer Convolutional Neural Networks Signal Processing, Computer-Assisted Snoring Humans
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Haemorrhage diagnosis in colour fundus images using a fast-convolutional neural network based on a modified U-Net.

Network (Bristol, England) Feb 12, 2024
Retinal haemorrhage stands as an early indicator of diabetic retinopathy, necessitating accurate detection for timely diagnosis. Addressing this need, this study proposes an enhanced machine-based diagnostic test for diabetic retinopathy through an u...
Diabetic Retinopathy Neural Networks, Computer Reproducibility of Results Humans Fundus Oculi Retinal Hemorrhage Sensitivity and Specificity Convolutional Neural Networks Image Processing, Computer-Assisted
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Convolutional neural network-based measurement of crown-implant ratio for implant-supported prostheses.

The Journal of prosthetic dentistry Jan 25, 2024
STATEMENT OF PROBLEM: Research has revealed that the crown-implant ratio (CIR) is a critical variable influencing the long-term stability of implant-supported prostheses in the oral cavity. Nevertheless, inefficient manual measurement and varied meas...
Dental Implants Dental Prosthesis Design Crowns Dental Prosthesis, Implant-Supported Humans Neural Networks, Computer Convolutional Neural Networks
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