AIMC Topic: Diagnosis, Computer-Assisted

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Two-Stage CNN Whole Heart Segmentation Combining Image Enhanced Attention Mechanism and Metric Classification.

Journal of digital imaging Sep 29, 2022
Accurate segmentation of multiple tissues and organs in cardiac medical imaging is of great value in computer-aided cardiovascular diagnosis. However, it is challenging due to the complex distribution of various tissues and organs in cardiac MRI (mag...
Neural Networks, Computer Diagnosis, Computer-Assisted Humans Heart Image Processing, Computer-Assisted Magnetic Resonance Imaging
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Atom Search Optimization with the Deep Transfer Learning-Driven Esophageal Cancer Classification Model.

Computational intelligence and neuroscience Sep 16, 2022
Esophageal cancer (EC) is a commonly occurring malignant tumor that significantly affects human health. Earlier recognition and classification of EC or premalignant lesions can result in highly effective targeted intervention. Accurate detection and ...
Machine Learning Esophageal Neoplasms Diagnosis, Computer-Assisted Humans Neural Networks, Computer
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Dermoscopic image segmentation based on Pyramid Residual Attention Module.

PloS one Sep 16, 2022
We propose a stacked convolutional neural network incorporating a novel and efficient pyramid residual attention (PRA) module for the task of automatic segmentation of dermoscopic images. Precise segmentation is a significant and challenging step for...
Humans Neural Networks, Computer Disease Progression Diagnosis, Computer-Assisted Skin Diseases Pyramidal Tracts
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Mammogram classification based on a novel convolutional neural network with efficient channel attention.

Computers in biology and medicine Sep 15, 2022
Early accurate mammography screening and diagnosis can reduce the mortality of breast cancer. Although CNN-based breast cancer computer-aided diagnosis (CAD) systems have achieved significant results in recent years, precise diagnosis of lesions in m...
Mammography Machine Learning Female Breast Neoplasms Diagnosis, Computer-Assisted Humans Neural Networks, Computer
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Diagnosis of Early Glottic Cancer Using Laryngeal Image and Voice Based on Ensemble Learning of Convolutional Neural Network Classifiers.

Journal of voice : official journal of the Voice Foundation Sep 6, 2022
OBJECTIVES: The purpose of study is to improve the classification accuracy by comparing the results obtained by applying decision tree ensemble learning, which is one of the methods to increase the classification accuracy for a relatively small datas...
Decision Trees Humans Video Recording Retrospective Studies Convolutional Neural Networks Male Early Detection of Cancer Diagnosis, Computer-Assisted Adult Voice Laryngeal Neoplasms Glottis Laryngoscopy Sound Recordings
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An Edge-Based Selection Method for Improving Regions-of-Interest Localizations Obtained Using Multiple Deep Learning Object-Detection Models in Breast Ultrasound Images.

Sensors (Basel, Switzerland) Sep 6, 2022
Computer-aided diagnosis (CAD) systems can be used to process breast ultrasound (BUS) images with the goal of enhancing the capability of diagnosing breast cancer. Many CAD systems operate by analyzing the region-of-interest (ROI) that contains the t...
Deep Learning Ultrasonography, Mammary Breast Neoplasms Diagnosis, Computer-Assisted Humans Female
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Detection and Analysis of Human Cells Based on Artificial Neural Network.

Computational intelligence and neuroscience Aug 31, 2022
The detection and classification of histopathological cell images is a hot topic in current research. Medical images are an important research direction and are widely used in computer-aided diagnosis, biological research, and other fields. A neural ...
Humans Diagnosis, Computer-Assisted Neural Networks, Computer Algorithms
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Cloud Computing-Based Framework for Breast Tumor Image Classification Using Fusion of AlexNet and GLCM Texture Features with Ensemble Multi-Kernel Support Vector Machine (MK-SVM).

Computational intelligence and neuroscience Aug 31, 2022
Breast cancer is common among women all over the world. Early identification of breast cancer lowers death rates. However, it is difficult to determine whether these are cancerous or noncancerous lesions due to their inconsistencies in image appearan...
Support Vector Machine Humans Cloud Computing Female Diagnosis, Computer-Assisted Image Processing, Computer-Assisted Aged Breast Neoplasms
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CheXGAT: A disease correlation-aware network for thorax disease diagnosis from chest X-ray images.

Artificial intelligence in medicine Aug 27, 2022
Chest X-ray (CXR) imaging is one of the most common diagnostic imaging techniques in clinical diagnosis and is usually used for radiological examinations to screen for thorax diseases. In this paper, we propose a novel computer-aided diagnosis (CAD) ...
Thorax X-Rays Diagnosis, Computer-Assisted Deep Learning Neural Networks, Computer
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Atrous residual convolutional neural network based on U-Net for retinal vessel segmentation.

PloS one Aug 22, 2022
Extracting features of retinal vessels from fundus images plays an essential role in computer-aided diagnosis of diseases, such as diabetes, hypertension, and cerebrovascular diseases. Although a number of deep learning-based methods have been used i...
Algorithms Disease Progression Diagnosis, Computer-Assisted Image Processing, Computer-Assisted Fundus Oculi Retinal Vessels Humans Neural Networks, Computer
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