AIMC Topic: Radiographic Image Interpretation, Computer-Assisted

Clear Filters Showing 341 to 350 of 1290 articles

Attention pyramid pooling network for artificial diagnosis on pulmonary nodules.

PloS one May 16, 2024
The development of automated tools using advanced technologies like deep learning holds great promise for improving the accuracy of lung nodule classification in computed tomography (CT) imaging, ultimately reducing lung cancer mortality rates. Howev...
Multiple Pulmonary Nodules Humans Solitary Pulmonary Nodule Lung Algorithms Neural Networks, Computer Radiographic Image Interpretation, Computer-Assisted Deep Learning Tomography, X-Ray Computed Lung Neoplasms
View on PubMed DOI

Artificial Intelligence-Enabled Quantitative Coronary Plaque and Hemodynamic Analysis for Predicting Acute Coronary Syndrome.

JACC. Cardiovascular imaging May 15, 2024
BACKGROUND: A lesion-level risk prediction for acute coronary syndrome (ACS) needs better characterization.
Middle Aged Risk Assessment Severity of Illness Index Hemodynamics Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Reproducibility of Results Coronary Artery Disease Risk Factors Time Factors Aged Humans Predictive Value of Tests Male Plaque, Atherosclerotic Artificial Intelligence Acute Coronary Syndrome Computed Tomography Angiography Prognosis Coronary Vessels Female Rupture, Spontaneous Coronary Circulation Multidetector Computed Tomography
View on PubMed DOI

Breast density prediction from low and standard dose mammograms using deep learning: effect of image resolution and model training approach on prediction quality.

Biomedical physics & engineering express May 15, 2024
. To improve breast cancer risk prediction for young women, we have developed deep learning methods to estimate mammographic density from low dose mammograms taken at approximately 1/10th of the usual dose. We investigate the quality and reliability ...
Image Processing, Computer-Assisted Mammography Radiographic Image Interpretation, Computer-Assisted Breast Radiation Dosage Female Reproducibility of Results Breast Neoplasms Humans Deep Learning Algorithms Breast Density
View on PubMed DOI

Interpretable multiphasic CT-based radiomic analysis for preoperatively differentiating benign and malignant solid renal tumors: a multicenter study.

Abdominal radiology (New York) May 11, 2024
BACKGROUND: To develop and compare machine learning models based on triphasic contrast-enhanced CT (CECT) for distinguishing between benign and malignant renal tumors.
Contrast Media Diagnosis, Differential Radiographic Image Interpretation, Computer-Assisted Kidney Neoplasms Retrospective Studies Tomography, X-Ray Computed Female Aged Humans Radiomics Machine Learning Male Aged, 80 and over Middle Aged Adult
View on PubMed DOI

Evaluation of image quality on low contrast media with deep learning image reconstruction algorithm in prospective ECG-triggering coronary CT angiography.

The international journal of cardiovascular imaging May 9, 2024
To assess the impact of low-dose contrast media (CM) injection protocol with deep learning image reconstruction (DLIR) algorithm on image quality in coronary CT angiography (CCTA). In this prospective study, patients underwent CCTA were prospectively...
Multidetector Computed Tomography Computed Tomography Angiography Cardiac-Gated Imaging Techniques Coronary Artery Disease Heart Rate Coronary Vessels Radiation Dosage Aged Male Middle Aged Deep Learning Predictive Value of Tests Coronary Angiography Radiographic Image Interpretation, Computer-Assisted Electrocardiography Contrast Media Humans Prospective Studies Female Reproducibility of Results
View on PubMed DOI

Impact of deep learning image reconstruction on volumetric accuracy and image quality of pulmonary nodules with different morphologies in low-dose CT.

Cancer imaging : the official publication of the International Cancer Imaging Society May 9, 2024
BACKGROUND: This study systematically compares the impact of innovative deep learning image reconstruction (DLIR, TrueFidelity) to conventionally used iterative reconstruction (IR) on nodule volumetry and subjective image quality (IQ) at highly reduc...
Humans Multiple Pulmonary Nodules Solitary Pulmonary Nodule Radiographic Image Interpretation, Computer-Assisted Radiation Dosage Phantoms, Imaging Tomography, X-Ray Computed Deep Learning Image Processing, Computer-Assisted Lung Neoplasms
View on PubMed DOI

Weakly-Supervised Segmentation-Based Quantitative Characterization of Pulmonary Cavity Lesions in CT Scans.

IEEE journal of translational engineering in health and medicine May 9, 2024
OBJECTIVE: Pulmonary cavity lesion is one of the commonly seen lesions in lung caused by a variety of malignant and non-malignant diseases. Diagnosis of a cavity lesion is commonly based on accurate recognition of the typical morphological characteri...
Lung Diseases Lung Supervised Machine Learning Humans Deep Learning Neural Networks, Computer Lung Neoplasms Algorithms Radiographic Image Interpretation, Computer-Assisted Tomography, X-Ray Computed
View on PubMed DOI

Deep learning-based fully automatic screening of carotid artery plaques in computed tomography angiography: a multicenter study.

Clinical radiology May 6, 2024
AIM: To develop and validate a deep learning (DL) algorithm for the automated detection and classification of carotid artery plaques (CAPs) on computed tomography angiography (CTA) images.
Retrospective Studies Female Carotid Arteries Aged Humans Male Plaque, Atherosclerotic Computed Tomography Angiography Sensitivity and Specificity Middle Aged Carotid Stenosis Deep Learning Carotid Artery Diseases Radiographic Image Interpretation, Computer-Assisted
View on PubMed DOI

ERetinaNet: An Efficient Neural Network Based on RetinaNet for Mammographic Breast Mass Detection.

IEEE journal of biomedical and health informatics May 6, 2024
Mammography is an effective method for diagnosing breast diseases, and computer-aided detection (CAD) systems play an important role in the detection of breast masses. However, low contrast and the interference of surrounding tissues make the detecti...
Female Breast Neoplasms Mammography Radiographic Image Interpretation, Computer-Assisted Humans Breast Neural Networks, Computer Algorithms
View on PubMed DOI

Interpretable machine learning based on CT-derived extracellular volume fraction to predict pathological grading of hepatocellular carcinoma.

Abdominal radiology (New York) May 4, 2024
PURPOSE: To develop a non-invasive auxiliary assessment method based on CT-derived extracellular volume (ECV) to predict the pathological grading (PG) of hepatocellular carcinoma (HCC).
Male Middle Aged Liver Neoplasms Carcinoma, Hepatocellular Female Aged Radiographic Image Interpretation, Computer-Assisted Predictive Value of Tests Adult Humans Sensitivity and Specificity Neoplasm Grading Machine Learning Retrospective Studies Tomography, X-Ray Computed
View on PubMed DOI
Popular Topics
Recent Journals