AIMC Topic: Convolutional Neural Networks

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Enhanced brain tumor detection and segmentation using densely connected convolutional networks with stacking ensemble learning.

Computers in biology and medicine Jan 24, 2025
- Brain tumors (BT), both benign and malignant, pose a substantial impact on human health and need precise and early detection for successful treatment. Analysing magnetic resonance imaging (MRI) image is a common method for BT diagnosis and segmenta...
Image Processing, Computer-Assisted Brain Neoplasms Magnetic Resonance Imaging Deep Learning Humans Ensemble Learning Convolutional Neural Networks Neural Networks, Computer Machine Learning Image Interpretation, Computer-Assisted
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An interpretable multi-scale convolutional attention residual neural network for glioma grading with Raman spectroscopy.

Analytical methods : advancing methods and applications Jan 23, 2025
Since the malignancy of gliomas varies with their grade, classifying gliomas of different grades can assist doctors in developing personalized surgical plans during surgery, thereby improving the prognosis. Raman spectroscopy is an optical method for...
Humans Neural Networks, Computer Machine Learning Convolutional Neural Networks Spectrum Analysis, Raman Glioma Algorithms Neoplasm Grading Brain Neoplasms Deep Learning
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Classifying the molecular subtype of breast cancer using vision transformer and convolutional neural network features.

Breast cancer research and treatment Jan 22, 2025
PURPOSE: Identification of the molecular subtypes in breast cancer allows to optimize treatment strategies, but usually requires invasive needle biopsy. Recently, non-invasive imaging has emerged as promising means to classify them. Magnetic resonanc...
Convolutional Neural Networks Female Mammography Breast Neoplasms Receptor, ErbB-2 Biomarkers, Tumor Humans Neural Networks, Computer
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A prospective and comparative study on improving the diagnostic accuracy of early gastric cancer based on deep convolutional neural network real-time diagnosis system (with video).

Surgical endoscopy Jan 22, 2025
BACKGROUND: Endoscopic diagnosis of early gastric cancer (EGC) is a challenge. It is not clear whether deep convolutional neural network (DCNN) model could improve the endoscopists' diagnostic performance.
Sensitivity and Specificity Male Middle Aged Female Deep Learning Convolutional Neural Networks Early Detection of Cancer Aged Stomach Neoplasms Video Recording Gastroscopy Neural Networks, Computer Prospective Studies Humans
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Systematic application of saliency maps to explain the decisions of convolutional neural networks for glaucoma diagnosis based on disc and cup geometry.

Biomedical physics & engineering express Jan 21, 2025
This paper systematically evaluates saliency methods as explainability tools for convolutional neural networks trained to diagnose glaucoma using simplified eye fundus images that contain only disc and cup outlines. These simplified images, a methodo...
Optic Disk Image Processing, Computer-Assisted Fundus Oculi Image Interpretation, Computer-Assisted Algorithms Humans Neural Networks, Computer Convolutional Neural Networks Glaucoma
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Convolutional neural networks for accurate real-time diagnosis of oral epithelial dysplasia and oral squamous cell carcinoma using high-resolution in vivo confocal microscopy.

Scientific reports Jan 20, 2025
Oral cancer detection is based on biopsy histopathology, however with digital microscopy imaging technology there is real potential for rapid multi-site imaging and simultaneous diagnostic analysis. Fifty-nine patients with oral mucosal abnormalities...
Humans Neural Networks, Computer Female Adult Male Carcinoma, Squamous Cell Aged Middle Aged Mouth Neoplasms Fluorescein Mouth Mucosa Acriflavine Convolutional Neural Networks Microscopy, Confocal
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Deep learning-based defect detection in film-coated tablets using a convolutional neural network.

International journal of pharmaceutics Jan 18, 2025
Film-coating is a critical step in pharmaceutical manufacturing. Traditional visual inspections for film-coated tablet defect assessment are subjective, inefficient, and labor-intensive. We propose a novel approach utilizing machine learning and imag...
Tablets, Enteric-Coated Neural Networks, Computer Drug Compounding Image Processing, Computer-Assisted Deep Learning Convolutional Neural Networks Technology, Pharmaceutical Tablets
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An open source convolutional neural network to detect and localize distal radius fractures on plain radiographs.

European journal of trauma and emergency surgery : official publication of the European Trauma Society Jan 17, 2025
PURPOSE: Distal radius fractures (DRFs) are often initially assessed by junior doctors under time constraints, with limited supervision, risking significant consequences if missed. Convolutional Neural Networks (CNNs) can aid in diagnosing fractures....
Humans Female Aged Aged, 80 and over Adult Neural Networks, Computer Algorithms Retrospective Studies Wrist Injuries Wrist Fractures Radiography Radius Fractures Trauma Centers Male Middle Aged Convolutional Neural Networks
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Convolutional neural network (CNN) configuration using a learning automaton model for neonatal brain image segmentation.

PloS one Jan 17, 2025
CNN is considered an efficient tool in brain image segmentation. However, neonatal brain images require specific methods due to their nature and structural differences from adult brain images. Hence, it is necessary to determine the optimal structure...
Convolutional Neural Networks Image Processing, Computer-Assisted Magnetic Resonance Imaging Algorithms Brain Infant, Newborn Humans Neural Networks, Computer
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Deep learning-based skin lesion analysis using hybrid ResUNet++ and modified AlexNet-Random Forest for enhanced segmentation and classification.

PloS one Jan 16, 2025
Skin cancer is considered globally as the most fatal disease. Most likely all the patients who received wrong diagnosis and low-quality treatment die early. Though if it is detected in the early stages the patient has fairly good chance and the afore...
Skin Random Forest Deep Learning Convolutional Neural Networks Image Processing, Computer-Assisted Algorithms Skin Neoplasms Humans Neural Networks, Computer
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