AIMC Topic: Image Interpretation, Computer-Assisted

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A combined model integrating radiomics and deep learning based on multiparametric magnetic resonance imaging for classification of brain metastases.

Acta radiologica (Stockholm, Sweden : 1987) Nov 18, 2024
BACKGROUND: Radiomics and deep learning (DL) can individually and efficiently identify the pathological type of brain metastases (BMs).
Image Interpretation, Computer-Assisted Adenocarcinoma of Lung Multiparametric Magnetic Resonance Imaging Female Deep Learning Lung Neoplasms Aged Humans Magnetic Resonance Imaging Brain Adult Feasibility Studies Radiomics Retrospective Studies Brain Neoplasms Male Middle Aged
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Artificial intelligence: a primer for pediatric radiologists.

Pediatric radiology Nov 18, 2024
Artificial intelligence (AI) is increasingly recognized for its transformative potential in radiology; yet, its application in pediatric radiology is relatively limited when compared to the whole of radiology. This manuscript introduces pediatric rad...
Humans Pediatrics Artificial Intelligence Radiology Image Interpretation, Computer-Assisted Child Radiologists
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The study on ultrasound image classification using a dual-branch model based on Resnet50 guided by U-net segmentation results.

BMC medical imaging Nov 18, 2024
In recent years, the incidence of nodular thyroid diseases has been increasing annually. Ultrasonography has become a routine diagnostic tool for thyroid nodules due to its high real-time capabilities and low invasiveness. However, thyroid images obt...
Ultrasonography Humans Thyroid Nodule Deep Learning Image Interpretation, Computer-Assisted Thyroid Gland
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Enhanced breast cancer diagnosis through integration of computer vision with fusion based joint transfer learning using multi modality medical images.

Scientific reports Nov 17, 2024
Breast cancer (BC) is a type of cancer which progresses and spreads from breast tissues and gradually exceeds the entire body; this kind of cancer originates in both sexes. Prompt recognition of this disorder is most significant in this phase, and it...
Female Breast Neoplasms Image Processing, Computer-Assisted Multimodal Imaging Image Interpretation, Computer-Assisted Humans Machine Learning Algorithms
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Deep Learning Reconstruction for Enhanced Resolution and Image Quality in Breath-Hold MRCP: A Preliminary Study.

Journal of computer assisted tomography Nov 13, 2024
OBJECTIVE: This preliminary study aims to assess the image quality of enhanced-resolution deep learning reconstruction (ER-DLR) in magnetic resonance cholangiopancreatography (MRCP) and compare it with non-ER-DLR MRCP images.
Aged, 80 and over Adult Male Middle Aged Retrospective Studies Humans Female Deep Learning Biliary Tract Diseases Aged Pancreatic Diseases Image Interpretation, Computer-Assisted Breath Holding Signal-To-Noise Ratio Cholangiopancreatography, Magnetic Resonance
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Segmentation of breast lesion using fuzzy thresholding and deep learning.

Computers in biology and medicine Nov 12, 2024
Breast cancer is a major cause of morbidity and mortality in women. In breast cancer screening, Dynamic Contrast Enhanced Magnetic Resonance Imaging (DCE-MRI) has shown promise as a technique, providing enhanced temporal patterns of breast tissues. T...
Magnetic Resonance Imaging Humans Fuzzy Logic Breast Neoplasms Image Interpretation, Computer-Assisted Female Breast Deep Learning
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Enhancing image-based diagnosis of gastrointestinal tract diseases through deep learning with EfficientNet and advanced data augmentation techniques.

BMC medical imaging Nov 12, 2024
The early detection and diagnosis of gastrointestinal tract diseases, such as ulcerative colitis, polyps, and esophagitis, are crucial for timely treatment. Traditional imaging techniques often rely on manual interpretation, which is subject to varia...
Humans Neural Networks, Computer Deep Learning Image Interpretation, Computer-Assisted Gastrointestinal Diseases
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High-precision MRI of liver and hepatic lesions on gadoxetic acid-enhanced hepatobiliary phase using a deep learning technique.

Japanese journal of radiology Nov 11, 2024
PURPOSE: The purpose of this study was to investigate whether the high-precision magnetic resonance (MR) sequence using modified Fast 3D mode wheel and Precise IQ Engine (PIQE), that was collected in a wheel shape with sequential data filling in the ...
Female Aged Aged, 80 and over Adult Humans Retrospective Studies Magnetic Resonance Imaging Liver Neoplasms Gadolinium DTPA Liver Male Imaging, Three-Dimensional Image Enhancement Image Interpretation, Computer-Assisted Middle Aged Liver Diseases Contrast Media Deep Learning
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Predicting malignancy in breast lesions: enhancing accuracy with fine-tuned convolutional neural network models.

BMC medical imaging Nov 11, 2024
BACKGROUND: This study aims to explore the accuracy of Convolutional Neural Network (CNN) models in predicting malignancy in Dynamic Contrast-Enhanced Breast Magnetic Resonance Imaging (DCE-BMRI).
Middle Aged ROC Curve Contrast Media Magnetic Resonance Imaging Aged Adult Breast Neoplasms Image Interpretation, Computer-Assisted Retrospective Studies Female Humans Neural Networks, Computer
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Detection of breast cancer using machine learning on time-series diffuse optical transillumination data.

Journal of biomedical optics Nov 11, 2024
SIGNIFICANCE: Optical mammography as a promising tool for cancer diagnosis has largely fallen behind expectations. Modern machine learning (ML) methods offer ways to improve cancer detection in diffuse optical transmission data.
Image Interpretation, Computer-Assisted Optical Imaging Transillumination Support Vector Machine Area Under Curve Breast Breast Neoplasms ROC Curve Machine Learning Image Processing, Computer-Assisted Female Humans
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