Radiology

[Deep learning-driven high-frequency ultrasound method for skin aging assessment].

Ultraviolet radiation is a primary external factor contributing to skin photoaging, as it induces cellular deoxyribonucleic acid damage and collagen degeneration, thereby accelerating skin aging and increasing the risk of skin cancer. Currently, skin aging assessment mainly relies on dermatologists' empirical judgment, which is inherently subjective and inefficient. To address these limitations, t...

[Research on electrical impedance tomography for pediatric pneumonia based on an improved radial basis function neural network].

In the diagnosis of pediatric pneumonia, the weak conductivity contrast of lung tissues leads to limited image resolution in electrical impedance tomography (EIT). To improve the quality of image reconstruction, this study proposes a radial basis function neural network optimized by the crested porcupine optimizer and adaptive moment estimation (CPOA-RBFNN). By integrating the global search capabi...

Reinforcement learning-driven adaptive game therapy for cognitive impairment patients with improved vision transformer based detection model.

BACKGROUND: Cognitive impairment is the growing challenge that requires early diagnosis and personalized management of neurodegenerative conditions li...

Integrating machine learning with histopathological, immunohistochemical, and PET parameters in the study of invasive breast carcinoma, no special type.

BACKGROUND: This study investigates the relationship between histopathological (HP) features, immunohistochemical (IHC) markers, 18F- FDG PET/CT param...

The optimal SVM model from multi-model comparison outperforms conventional criteria in preoperative prediction of ovarian cancer residual disease.

OBJECTIVE: To develop an interpretable artificial intelligence (AI)-based machine learning model integrating 18F-fluorodeoxyglucose positron emission ...

Development and validation of a multimodal artificial intelligence-based model for predicting post-prostatectomy treatment outcomes from baseline biparametric prostate magnetic resonance imaging.

PURPOSE: Prostate cancer (PCa) is the second most common cancer and cause of cancer deaths among American men. Existing risk prediction methods have l...

SegJointGene: joint cell segmentation and spatial gene prioritization by information entropy guided convolutional neural networks.

MOTIVATION: Spatial sequencing technologies enable the single-cell-level study of molecular organization in tissues. Revealing such spatial patterns r...

Evaluating expert decision-pattern alignment in endovascular planning for intracranial aneurysms using a multimodal large language model.

BACKGROUND: Endovascular treatment planning for intracranial aneurysms requires integrating vascular geometry, branch preservation, device feasibility...

CT in adult patients with Polytrauma: current practices, protocol optimization, structured reporting and future directions.

Computed tomography [CT] is the frontline imaging modality for the assessment of polytrauma patients because of its speed, diagnostic accuracy and inf...

Hypoperfusion Intensity Ratio as a Predictive Marker in Pre-Endovascular Treatment Perfusion MRI for Acute Middle Cerebral Artery Occlusion with Intracranial Atherosclerosis.

Introduction Identifying the cause of MCA occlusion before endovascular treatment (EVT) in acute ischemic stroke is useful. Hypoperfusion intensity ra...

DGCD-3D: Difference-guided conditional diffusion model for low-field 3D MRI enhancement to assist stroke assessment.

Low-field (LF) magnetic resonance imaging (MRI) plays a crucial role in assisting clinicians with rapid stroke diagnosis. However, its inherent limita...

Multicenter evaluation of real-time artificial intelligence assistance for carotid artery stenting.

BACKGROUND: Unintended device movement during carotid artery stenting (CAS) may lead to procedural complications. Our previous preliminary single-cent...

Diagnosis of Small Focal Liver Lesions (≤2 cm): A Deep Learning Approach Based on B-Mode Ultrasound and Contrast-Enhanced Ultrasound.

BACKGROUND: To develop and validate a deep learning (DL) model based on feature fusion with B-mode ultrasound (BMUS) and contrast enhanced ultrasound ...

Enhanced brain tumour prediction using quantum: a hybrid deep learning approach.

Brain tumours are very serious concerns in the health field; they should be diagnosed properly and at the right time to ensure treatment efficacy. Whi...

Deep transfer learning for detection of placenta-mediated diseases from ultrasound images.

Placenta-mediated diseases, such as preeclampsia (PE) and small-for-gestational-age (SGA) neonates, are associated with structural and functional chan...

Spatially identifying regions of tumor recurrence in patients with suspected recurrent glioma using physiologic MRI and machine learning.

Despite prior success in classifying recurrent glioma noninvasively with multi-parametric MRI and AI, clinical applicability has yet to be demonstrate...

Feasibility of deep learning-accelerated ultrafast T1-weighted VIBE Dixon imaging of the pelvis for screening of metastases in prostate MRI.

OBJECTIVE: This study aims to assess the image quality and perceived diagnostic confidence of research deep learning (DL)-accelerated T1-weighted "vol...

Roles and applications of artificial intelligence in fetal and placental MRI: a literature review.

BACKGROUND: Artificial intelligence (AI) has been increasingly integrated with fetal and placental magnetic resonance imaging (MRI) to enhance the det...

Discrimination of generalized anxiety and major depressive disorders by machine learning of resting-state functional MRI.

OBJECTIVE: To address the clinical difficulty of differentiating Generalized Anxiety Disorder (GAD) from Major Depressive Disorder (MDD), this study a...

Development and validation of an interpretable ultrasound radiomics model for benign and malignant classification of breast lesions: a multicenter large-sample study.

OBJECTIVES: To develop and validate a combined ultrasound-based radiomics-clinical model for differentiating benign and malignant breast lesions. MATE...