AIMC Topic: Calcinosis

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Deep learning approaches for differentiating thyroid nodules with calcification: a two-center study.

BMC cancer Nov 23, 2023
BACKGROUND: Calcification is a common phenomenon in both benign and malignant thyroid nodules. However, the clinical significance of calcification remains unclear. Therefore, we explored a more objective method for distinguishing between benign and m...
Calcinosis Thyroid Nodule ROC Curve Humans Retrospective Studies Deep Learning Ultrasonography
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Deep learning performance for detection and classification of microcalcifications on mammography.

European radiology experimental Nov 7, 2023
BACKGROUND: Breast cancer screening through mammography is crucial for early detection, yet the demand for mammography services surpasses the capacity of radiologists. Artificial intelligence (AI) can assist in evaluating microcalcifications on mammo...
Humans Artificial Intelligence Deep Learning Calcinosis Mammography Retrospective Studies Female Breast Neoplasms
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Multitask deep learning on mammography to predict extensive intraductal component in invasive breast cancer.

European radiology Oct 9, 2023
OBJECTIVES: To develop a multitask deep learning (DL) algorithm to automatically classify mammography imaging findings and predict the existence of extensive intraductal component (EIC) in invasive breast cancer.
Breast Neoplasms Mammography Deep Learning Breast Calcinosis Humans Female
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A novel approach to quantify calcifications of thyroid nodules in US images based on deep learning: predicting the risk of cervical lymph node metastasis in papillary thyroid cancer patients.

European radiology Jul 12, 2023
OBJECTIVE: Based on ultrasound (US) images, this study aimed to detect and quantify calcifications of thyroid nodules, which are regarded as one of the most important features in US diagnosis of thyroid cancer, and to further investigate the value of...
Deep Learning Thyroid Neoplasms Thyroid Nodule Retrospective Studies Risk Factors Carcinoma Carcinoma, Papillary Thyroid Cancer, Papillary Lymph Nodes Lymphatic Metastasis Calcinosis Humans
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Can convolutional neural networks identify external carotid artery calcifications?

Oral surgery, oral medicine, oral pathology and oral radiology Apr 20, 2023
OBJECTIVE: We developed and evaluated the accuracy and reliability of a convolutional neural network (CNN) in detecting external carotid artery calcifications (ECACs) in cone beam computed tomography scans.
Carotid Artery, External Carotid Artery Diseases Radiographic Image Interpretation, Computer-Assisted Vascular Calcification Reproducibility of Results Humans Middle Aged Aged Neural Networks, Computer Cone-Beam Computed Tomography Male Female Calcinosis
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Calcification Detection in Intravascular Ultrasound (IVUS) Images Using Transfer Learning Based MultiSVM model.

Ultrasonic imaging Apr 13, 2023
Cardiovascular disease serves as the leading cause of death worldwide. Calcification detection is considered an important factor in cardiovascular diseases. Currently, medical practitioners visually inspect the presence of calcification using intrava...
Machine Learning Ultrasonography Calcinosis Ultrasonography, Interventional Humans
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Deep learning-regularized, single-step quantitative susceptibility mapping quantification.

NMR in biomedicine Nov 23, 2022
The purpose of the current study was to develop deep learning-regularized, single-step quantitative susceptibility mapping (QSM) quantification, directly generating QSM from the total phase map. A deep learning-regularized, single-step QSM quantifica...
Humans Algorithms Brain Deep Learning Calcinosis Image Processing, Computer-Assisted Brain Mapping Magnetic Resonance Imaging
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Visual and quantitative evaluation of microcalcifications in mammograms with deep learning-based super-resolution.

European journal of radiology Jul 6, 2022
PURPOSE: To evaluate visually and quantitatively the performance of a deep-learning-based super-resolution (SR) model for microcalcifications in digital mammography.
Female Deep Learning Reproducibility of Results Calcinosis Mammography Adult Humans Breast Neoplasms Artificial Intelligence Middle Aged
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Deep Learning Capabilities for the Categorization of Microcalcification.

International journal of environmental research and public health Feb 14, 2022
Breast cancer is the most common cancer in women worldwide. It is the most frequently diagnosed cancer among women in 140 countries out of 184 reporting countries. Lesions of breast cancer are abnormal areas in the breast tissues. Various types of br...
Breast Neoplasms Deep Learning Calcinosis Neural Networks, Computer Female Humans Mammography
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A convolutional deep learning model for improving mammographic breast-microcalcification diagnosis.

Scientific reports Dec 14, 2021
This study aimed to assess the diagnostic performance of deep convolutional neural networks (DCNNs) in classifying breast microcalcification in screening mammograms. To this end, 1579 mammographic images were collected retrospectively from patients e...
Calcinosis Mammography Breast Breast Diseases Humans Female Databases, Factual Deep Learning Models, Theoretical
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