AIMC Topic:
Image Interpretation, Computer-Assisted

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A novel enhanced softmax loss function for brain tumour detection using deep learning.

Journal of neuroscience methods Nov 14, 2019
BACKGROUND AND AIM: In deep learning, the sigmoid function is unsuccessfully used for the multiclass classification of the brain tumour due to its limit of binary classification. This study aims to increase the classification accuracy by reducing the...
Magnetic Resonance Imaging Image Interpretation, Computer-Assisted Neuroimaging Humans Brain Neoplasms Deep Learning
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Brain pathology identification using computer aided diagnostic tool: A systematic review.

Computer methods and programs in biomedicine Nov 13, 2019
Computer aided diagnostic (CAD) has become a significant tool in expanding patient quality-of-life by reducing human errors in diagnosis. CAD can expedite decision-making on complex clinical data automatically. Since brain diseases can be fatal, rapi...
Image Interpretation, Computer-Assisted Brain Diseases Neuroimaging Dementia, Vascular Humans Neural Networks, Computer Image Processing, Computer-Assisted Brain Algorithms Magnetic Resonance Imaging Brain Neoplasms Computers Sarcoma Diagnosis, Computer-Assisted Alzheimer Disease Deep Learning
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Using multi-layer perceptron with Laplacian edge detector for bladder cancer diagnosis.

Artificial intelligence in medicine Nov 13, 2019
In this paper, the urinary bladder cancer diagnostic method which is based on Multi-Layer Perceptron and Laplacian edge detector is presented. The aim of this paper is to investigate the implementation possibility of a simpler method (Multi-Layer Per...
Artificial Intelligence Humans Urinary Bladder Urinary Bladder Neoplasms Neural Networks, Computer Algorithms Area Under Curve Image Interpretation, Computer-Assisted Databases, Factual Cystoscopy Deep Learning
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Three-dimensional Deep Convolutional Neural Networks for Automated Myocardial Scar Quantification in Hypertrophic Cardiomyopathy: A Multicenter Multivendor Study.

Radiology Nov 12, 2019
Background Cardiac MRI late gadolinium enhancement (LGE) scar volume is an important marker for outcome prediction in patients with hypertrophic cardiomyopathy (HCM); however, its clinical application is hindered by a lack of measurement standardizat...
Imaging, Three-Dimensional Magnetic Resonance Imaging Cicatrix Myocardium Male Middle Aged Adolescent Child Heart Image Interpretation, Computer-Assisted Cardiomyopathy, Hypertrophic Neural Networks, Computer Retrospective Studies Female Reproducibility of Results Aged Aged, 80 and over Young Adult Adult Humans
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Clear cell renal cell carcinoma: Machine learning-based computed tomography radiomics analysis for the prediction of WHO/ISUP grade.

European journal of radiology Nov 6, 2019
PURPOSE: To evaluate the performance of machine learning (ML)-based computed tomography (CT) radiomics analysis for discriminating between low grade (WHO/ISUP I-II) and high grade (WHO/ISUP III-IV) clear cell renal cell carcinomas (ccRCCs).
Humans Carcinoma, Renal Cell Machine Learning Algorithms Retrospective Studies Middle Aged Kidney Logistic Models Aged, 80 and over Neoplasm Grading Support Vector Machine Diagnosis, Differential Young Adult Tomography, X-Ray Computed Image Interpretation, Computer-Assisted Adult Predictive Value of Tests Kidney Neoplasms Female Male Reproducibility of Results Aged
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Computer-assisted assessment of colonic polyp histopathology using probe-based confocal laser endomicroscopy.

International journal of colorectal disease Nov 6, 2019
INTRODUCTION: Probe-based confocal laser endomicroscopy (pCLE) is a promising modality for classifying polyp histology in vivo, but decision making in real-time is hampered by high-magnification targeting and by the learning curve for image interpret...
Machine Learning Female Reproducibility of Results Aged Aged, 80 and over Humans Colonic Neoplasms Tumor Burden Colonic Polyps Image Interpretation, Computer-Assisted Observer Variation Clinical Competence Microscopy, Confocal Predictive Value of Tests Feasibility Studies Male Middle Aged Colonoscopy Diagnosis, Computer-Assisted
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Pulmonary Textures Classification via a Multi-Scale Attention Network.

IEEE journal of biomedical and health informatics Nov 4, 2019
Precise classification of pulmonary textures is crucial to develop a computer aided diagnosis (CAD) system of diffuse lung diseases (DLDs). Although deep learning techniques have been applied to this task, the classification performance is not satisf...
Image Processing, Computer-Assisted Lung Diseases Image Interpretation, Computer-Assisted Tomography, X-Ray Computed Humans Lung Deep Learning
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Automated Breast Cancer Diagnosis Based on Machine Learning Algorithms.

Journal of healthcare engineering Nov 3, 2019
There have been several empirical studies addressing breast cancer using machine learning and soft computing techniques. Many claim that their algorithms are faster, easier, or more accurate than others are. This study is based on genetic programming...
Breast Humans Female Image Interpretation, Computer-Assisted Machine Learning Reproducibility of Results Algorithms Sensitivity and Specificity Databases, Factual Breast Neoplasms
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Diagnostic performance of machine learning applied to texture analysis-derived features for breast lesion characterisation at automated breast ultrasound: a pilot study.

European radiology experimental Nov 1, 2019
BACKGROUND: Our aims were to determine if features derived from texture analysis (TA) can distinguish normal, benign, and malignant tissue on automated breast ultrasound (ABUS); to evaluate whether machine learning (ML) applied to TA can categorise A...
Machine Learning Retrospective Studies Female Aged Humans Pilot Projects Diagnosis, Differential Ultrasonography, Mammary Image Interpretation, Computer-Assisted Breast Diseases Aged, 80 and over Adult Breast Neoplasms Middle Aged
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Deep learning, reusable and problem-based architectures for detection of consolidation on chest X-ray images.

Computer methods and programs in biomedicine Oct 31, 2019
BACKGROUND AND OBJECTIVE: In most patients presenting with respiratory symptoms, the findings of chest radiography play a key role in the diagnosis, management, and follow-up of the disease. Consolidation is a common term in radiology, which indicate...
Datasets as Topic X-Rays Humans Deep Learning Algorithms Data Interpretation, Statistical Lung Diseases Image Interpretation, Computer-Assisted
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