Radiology

The automatic diagnosis artificial intelligence system for preoperative magnetic resonance imaging of uterine sarcoma.

OBJECTIVE: Magnetic resonance imaging (MRI) is efficient for the diagnosis of preoperative uterine sarcoma; however, misdiagnoses may occur. In this study, we developed a new artificial intelligence (AI) system to overcome the limitations of requiring specialists to manually process datasets and a large amount of computer resources.

Ultrasound-guided sciatic nerve block in Wistar rat cadavers: Relevant anatomy and injection distribution.

OBJECTIVE: To investigate the feasibility of an ultrasound-guided sciatic nerve block by describing the sonoanatomy and comparing the distribution of two volumes of bupivacaine dye solution for nerve staining.

CEMRI-Based Quantification of Intratumoral Heterogeneity for Predicting Aggressive Characteristics of Hepatocellular Carcinoma Using Habitat Analysis: Comparison and Combination of Deep Learning.

RATIONALE AND OBJECTIVES: To explore both an intratumoral heterogeneity (ITH) model based on habitat analysis and a deep learning (DL) model based on ...

Contrast-Enhanced CT-Based Deep Learning Radiomics Nomogram for the Survival Prediction in Gallbladder Cancer.

RATIONALE AND OBJECTIVES: An accurate prognostic model is essential for the development of treatment strategies for gallbladder cancer (GBC). This stu...

BASE: Brain Age Standardized Evaluation.

Brain age, most commonly inferred from T1-weighted magnetic resonance images (T1w MRI), is a robust biomarker of brain health and related diseases. Su...

Deep learning-driven multi-view multi-task image quality assessment method for chest CT image.

BACKGROUND: Chest computed tomography (CT) image quality impacts radiologists' diagnoses. Pre-diagnostic image quality assessment is essential but lab...

Retracted: Artificial Intelligence Technology Combined with Ultrasound-Guided Needle Knife Interventional Treatment of PF: Improvement of Pain, Fascia Thickness, and Ankle-Foot Function in Patients.

[This retracts the article DOI: 10.1155/2022/3021320.].

Retracted: Application of Artificial Intelligence in Radiotherapy of Nasopharyngeal Carcinoma with Magnetic Resonance Imaging.

[This retracts the article DOI: 10.1155/2022/4132989.].

Unveiling the future of breast cancer assessment: a critical review on generative adversarial networks in elastography ultrasound.

Elastography Ultrasound provides elasticity information of the tissues, which is crucial for understanding the density and texture, allowing for the d...

Deep learning radiomics of multimodal ultrasound for classifying metastatic cervical lymphadenopathy into primary cancer sites: a feasibility study.

PURPOSE: To investigate the feasibility of deep learning radiomics (DLR) based on multimodal ultrasound to differentiate the primary cancer sites of m...

Deep learning approach for discrimination of liver lesions using nine time-phase images of contrast-enhanced ultrasound.

PURPOSE: Contrast-enhanced ultrasound (CEUS) shows different enhancement patterns depending on the time after administration of the contrast agent. Th...

A Systematic Literature Review of 3D Deep Learning Techniques in Computed Tomography Reconstruction.

Computed tomography (CT) is used in a wide range of medical imaging diagnoses. However, the reconstruction of CT images from raw projection data is in...

Prognosis Forecast of Re-Irradiation for Recurrent Nasopharyngeal Carcinoma Based on Deep Learning Multi-Modal Information Fusion.

Radiation therapy is the primary treatment for recurrent nasopharyngeal carcinoma. However, it may induce necrosis of the nasopharynx, leading to seve...

Using Artificial Intelligence to Semi-Quantitate Coronary Calcium as an 'Incidentaloma' on Non-Gated, Non-Contrast CT Scans, A Single-Center Descriptive Study in West Michigan.

INTRODUCTION: Non-gated, non-contrast computed tomography (CT) scans are commonly ordered for a variety of non-cardiac indications, but do not routine...

Deep UV-excited fluorescence microscopy installed with CycleGAN-assisted image translation enhances precise detection of lymph node metastasis towards rapid intraoperative diagnosis.

Rapid and precise intraoperative diagnosing systems are required for improving surgical outcomes and patient prognosis. Because of the poor quality an...

A novel loss function to reproduce texture features for deep learning-based MRI-to-CT synthesis.

BACKGROUND: Studies on computed tomography (CT) synthesis based on magnetic resonance imaging (MRI) have mainly focused on pixel-wise consistency, but...

Dynamic parametric MRI and deep learning: Unveiling renal pathophysiology through accurate kidney size quantification.

Renal pathologies often manifest as alterations in kidney size, providing a valuable avenue for employing dynamic parametric MRI as a means to derive ...

One-Stop Automated Diagnostic System for Carpal Tunnel Syndrome in Ultrasound Images Using Deep Learning.

OBJECTIVE: Ultrasound (US) examination has unique advantages in diagnosing carpal tunnel syndrome (CTS), although identification of the median nerve (...

A Deep Learning-Based Ensemble Method for Early Diagnosis of Alzheimer's Disease using MRI Images.

Recently, the early diagnosis of Alzheimer's disease has gained major attention due to the growing prevalence of the disease and the resulting costs i...

Rapid intraoperative multi-molecular diagnosis of glioma with ultrasound radio frequency signals and deep learning.

BACKGROUND: Molecular diagnosis is crucial for biomarker-assisted glioma resection and management. However, some limitations of current molecular diag...