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Breast cancer remains the most commonly diagnosed malignancy among women worldwide. Histopathological image analysis is the clinical gold standard for diagnosis; however, the high resolution and complexity of ...
This study aims to investigate the clinical utility of multiparametric MRI features in distinguishing between germinal center B-cell-like (GCB) and non-germinal center B-cell-like (non-GCB) subtypes of primary...
In breast magnetic resonance imaging (MRI), the differentiation between benign and malignant breast masses relies on the Breast Imaging Reporting and Data System Magnetic Resonance Imaging (BI-RADS-MRI) lexico...
This study assessed the prognostic value of non-alcoholic fatty liver disease (NAFLD) in predicting major adverse cardiovascular events (MACE) in patients with suspected coronary artery disease (CAD), using co...
To develop and validate radiomics and deep learning models based on Gd-EOB-DTPA enhanced MRI for differentiation between hepatocellular carcinoma (HCC) and focal nodular hyperplasia (FNH) showing iso- or hyper...
Approximately 20% to 30% of preterm infants may develop white matter injury. Early detection of brain injury is of great significance for clinical practice. The snake model is a boundary detection technology u...
Medical image segmentation is a critical task for the early detection and diagnosis of various conditions, such as skin cancer, polyps, thyroid nodules, and pancreatic tumors. Recently, deep learning architect...
Quantitative assessment of peripheral nerve viscoelasticity is important for understanding nerve physiology and detecting early neuropathic changes. However, reference values for the viscosity and stiffness of...
Breast cancer is one of the most prevalent malignancies among women worldwide and remains a major public health concern. Accurate classification of breast tumor subtypes is essential for guiding treatment deci...
Accurate preoperative assessment of central lymph nodes is crucial for determining the extent of surgery for papillary thyroid microcarcinoma (PTMC). Patients who are clinically lymph node negative (cN0) lack ...
To assess the clinical characteristics and CT findings associated with epidermal growth factor receptor (EGFR) mutation status in stage III-IV solid lung adenocarcinoma (LAD) patients.
To evaluate the performance of contrast-enhanced cone-beam breast CT (CE-CBBCT) using visual, quantitative, and combined models in distinguishing pathological complete response (pCR) from minimal residual dise...
To investigate the value of computed tomography imaging features combined with clinicopathological factors in predicting patients’ biliary stricture (BS) after liver transplantation and to identify patients at...
To investigate the imaging characteristics of the hepatocyte-specific contrast agent gadolinium-ethoxybenzyl-diethylenetriamine pentaacetic acid (Gd-EOB-DTPA) in inflammatory hepatocellular adenoma.
Perivascular space (PVS) has recently gained attention as a neurological indicator. However, there is still limited research on the relationship between basal ganglia PVS (BG-PVS) volume and neurodevelopmental...
To develop a multimodal magnetic resonance imaging (MRI)-based spatial mapping framework for quantitatively characterizing intratumoral heterogeneity in recurrent glioblastoma (rGBM), identifying distinct imag...
To develop a deep learning segmentation method utilizing the nnU-Net architecture for fully automated whole-breast segmentation based on diffusion-weighted imaging (DWI) and synthetic MRI (SyMRI) images.
Noninvasive isocitrate dehydrogenase (IDH) genotyping in gliomas remains a critical challenge. This study investigates the performance of the whole-tumor histogram analysis of neurite orientation dispersion an...
Motion artifacts caused by respiration, cardiac pulsation, and vascular flow often degrade image quality in conventional contrast-enhanced transverse T1-weighted magnetic resonance imaging (MRI) of the thoraci...
Radiofrequency Echographic Multi Spectrometry (REMS) is a portable and radiation-free technology that can evaluate and monitor osteoporosis. In particular, REMS has been shown to measure bone mineral density (...
The objective of this study was to assess the prevalence and morphometric characteristics of the genial tubercle (GT) in a Turkish population using cone-beam computed tomography (CBCT), by classifying the morp...
This study aimed to quantitatively and noninvasively assess diaphragmatic alterations in patients with end-stage renal disease undergoing hemodialysis (HD) or peritoneal dialysis (PD) using ultrasonography (US...
Tuberculosis (TB) is a serious infectious disease that remains a global health challenge. While chest X-rays (CXRs) are widely used for TB detection, manual interpretation can be subjective and time-consuming....
Numerous studies have shown that patients with Azheimer’s disease (AD) or amnestic mild cognitive impairment (aMCI) have atrophy in the hippocampus and amygdala. However, there are few MRI studies that have jo...
Programmed death-ligand 1 (PD-L1) is a key biomarker for nasopharyngeal carcinoma (NPC) immunotherapy. However, given that it requires an invasive approach based on immunohistochemical testing, novel non-invas...
This study aimed to analyze the ultrasound features of snakebite-affected limbs and explore the diagnostic utility of multimodal ultrasound.
Prostate-specific membrane antigen (PSMA) PET/CT plays an increasing role in prostate cancer management. Radiomics analysis of PSMA PET/CT images may provide additional information for risk stratification. Thi...
To explore the stratification and identification of adrenal lipid-poor adenomas (LPAs), adrenal cysts (ACs), and adrenal ganglioneuromas (AGNs) from each other using contrast-enhanced computed tomography (CT).
This study aimed to develop and validate a nomogram to predict both the tumor-stroma ratio (TSR) and the overall survival (OS) of patients with pancreatic ductal adenocarcinoma (PDAC) using preoperative dual-e...
Deep learning necessitates a substantial amount of data, yet obtaining sufficient medical images is difficult due to concerns about patient privacy and high collection costs.
This study endeavors to systematically investigate factors influencing knee joint stability following anterior cruciate ligament reconstruction (ACLR) using magnetic resonance imaging (MRI), with the goal of p...
To evaluate the efficacy of single-energy metal artifact reduction (SEMAR) algorithm in removing metallic artifacts for patients with novel leadless pacemakers (PMs) compared to those with conventional transve...
Deep learning-accelerated single-shot turbo-spin-echo techniques (DL-HASTE) enable single-breath-hold T2-weighted abdominal imaging. However, studies evaluating the image quality of DL-HASTE with and without f...
The Deauville score is a key prognostic factor in Hodgkin lymphoma (HL) and diffuse large B-cell lymphoma (DLBCL) during interim and end-of-treatment PET/CT evaluations. However, additional measurements, parti...
The aim of this study was to evaluate the feasibility of dual-energy computed tomography (DECT)-derived collagen density mapping of the temporomandibular disc and to analyze the association with CT-detected jo...
Abdominal aortic aneurysms (AAA) pose a serious rupture risk, heightened by aortic calcification. Traditional calcification scoring methods are slow and require expertise. This study aims to construct a convol...
The original article was published in BMC Medical Imaging 2025 25:327
Cone-beam computed tomography (CBCT) is a widely used imaging technique. In practical applications, reducing projection views can decrease radiation exposure and accelerate scanning speed, with potential benef...
Proliferative hepatocellular carcinoma (HCC) is an aggressive tumor with varying prognosis depending on the different disease stages and subsequent treatment. This study aims to develop and validate a deep lea...
Developing quantitative methods to assess post-surgery treatment response in Glioblastoma Multiforme (GBM) is critical for improving patient outcomes and refining current subjective approaches. This study anal...
Assessing lymph node metastasis (LNM) involvement in patients with rectal cancer (RC) is fundamental in disease management. In this study, we used artificial intelligence (AI) technology to develop a segmentat...
This study introduces MSFE-GallNet-X, a domain-adaptive deep learning model utilizing multi-scale feature extraction (MSFE) to improve the classification accuracy of gallbladder diseases from grayscale ultraso...
The combination of dynamic-contrast-enhanced-magnetic-resonance-imaging (DCE-MRI) with the apparent-diffusion-coefficient (ADC) holds significant value for predicting tumor pathological outcomes. This study pi...
Contrast-enhanced ultrasound (CEUS) is increasingly used in the characterization of cystic renal lesions. Bosniak IIF lesions warrant follow-up, and their reported progression rate remains variable.
Perivascular adipose tissue has been shown to play a role in cardiovascular disease. This provides evidences that perivascular fat density (PFD) may have a correlation with abdominal aortic aneurysm (AAA). The...
Brain age estimation is an emerging biomarker for assessing neurodegeneration in multiple sclerosis (MS). However, MS-related lesions can distort structural measurements, potentially leading to inaccuracies in...
Diabetic tibial nerve neuropathy (DTN), a severe subtype of diabetic peripheral neuropathy, is often underdiagnosed in the early stages. This significantly raises the risks of foot ulcers and amputations. This...
Hydronephrosis is a common finding on renal ultrasound, but its physiological causes-such as hydration-induced distention-remain under-recognized in healthy individuals. Misinterpreting such cases as pathologi...
Advanced MR imaging methods, such as perfusion, spectroscopy and diffusion-weighted imaging (DWI), help to distinguish between different types of brain tumors. We have established a rapid wash-out and late-enh...
Pathological diagnosis is important for the treatment of deep suprahyoid head and neck lesions, and tissue sampling needs to balance minimal invasiveness and accuracy. The purpose of this study was to evaluate...
Citation Impact
Journal Impact Factor: 3.2 (2024)
5-year Journal Impact Factor: 3.1 (2024)
Source Normalized Impact per Paper (SNIP): 1.229 (2024)
SCImago Journal Rank (SJR): 0.701 (2024)
Speed
Submission to first editorial decision (median days): 13
Submission to acceptance (median days): 127
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Downloads: 1,190,622
Altmetric mentions: 86
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